Re: [music-dsp] Errata in The Art of VA Filter Design 2.1.0
On 26-Jan-19 18:25, Giulio Moro wrote: Hi there, really appreciate your VA book. I am reading version 2.1.0 and I think I spotted an error: on page 93, the text goes: "In this respect consider that Fig. 3.12 is trying to explicitly emulate the analog integration behavior, preserving the topology of the original analog structure, while Fig. 3.34 is concerned solely with implementing a correct transfer function. Since Fig. 3.34 implements a classical approach to the bilinear transform application for digital filter design (which ignores the filter topology) we’ll refer to the trapezoidal integration replacement technique as the topology-preserving bilinear transform (or, shortly, TPBLT)." I *think* that it should be "Since Fig. 3.12 implements ..." instead of 3.34. Am I right? If I am not, then I guess I did not understand much about TPT :) Hi, no, the text is correct at this point. 3.34 implements a classical version of the filter, which is bilinear transform without preserving the topology, while 3.12 preserves it, thus we refer to 3.12 as topology-preserving bilinear transform. (and for the reference of others, who might be reading this, the page number is actually 81, while 93 is the "raw" page number, depending on your PDF viewer you might need to look for one or the other) PS: any chance there could be a permalink to the most recent version of the book? I seem that I have to go back through the archives of music-dsp to find the most recent link (or manually attempt a URL for version 2.1.1). https://www.kvraudio.com/forum/viewtopic.php?t=350246 (if you google for "the art of va filter design" this is one of the first links) Also, is the book linked to from anywhere on the NI website? It is linked from the Reaktor area of the website. The current URL is https://www.native-instruments.com/en/products/komplete/synths/reaktor-6/dsp-articles/ Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] The art of VA filter design - video
On 28-Nov-18 11:07, Jean-Baptiste Thiebaut wrote: I'm proud to share this video of Vadim Zavalishin, who came to ADC in London last week to share his DSP knowledge. I came across Vadim's work on this list and invited him to ADC a few months ago, and thought I'd share this with you. (I hope you don't mind, Vadim). No, of course I don't ;) Thank you for sharing this and thanks again for inviting me to the ADC. It has been lots of fun watching the talks and meeting other people from the industry (and even some of my former NI colleagues going as far back as 2001). Best regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] zero delay feedback for phase modulation synthesis?
I think people have thought about this (IIRC at least I heard from one of the U-He guys that he tried zero-delay feedback FM). I'm not sure what's the origin of your equation, but then I'm not into phase modulation synthesis. Anyway, I suspect in certain excessive nonlinear situations there is no solution whatsoever. E.g. consider the zero-feedback equation of the form x = a*x + b*y y = b*x - a*y where x,y are signals and a and b are coefficients such that a^2+b^2=1 (actually this equation is linear, but I think you get the idea). Some basic thoughts on the rising issues (and on how to solve your equation) can be found in Section 3.13 of this text: https://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign_2.1.0.pdf Plus the usual numerical nonlinear solution techniques of course (where Sections 6.4-6.8 and 6.10 may be of interest). Regards, Vadim On 15-Nov-18 20:55, gm wrote: I wonder if anyone has thought about this? I am aware that it may have little practical use and may actually worsen the "fractal noise" behaviour at higher feedback levels. (Long ago I tested this with a tuned delay in the feedback path and thats what I recall) But still I am interested. If the recurrence for the oscillator with feedback is: y[n] = ( 1/(2Pi) * sine(2*Pi* y[n-1]) + k) mod 1 there are two nonlinearities and it's all above my head... ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Book: The Art of VA Filter Design 2.1.0
On 01-Nov-18 16:16, Fabian-Robert Stöter wrote: I appreciate that but it would still be nice if your book could be cited appropriately. Have you thought about putting it on arxiv or zenodo.org <http://zenodo.org>? This would give you the possibility to version the book and make folks from academia happy with a proper DOI reference. Nobody complained so far, but I will consider your suggestion, thank you! Best regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Book: The Art of VA Filter Design 2.1.0
On 02-Nov-18 03:06, Andrew Simper wrote: If you prize symmetry then you can use a cascade with 2 x one pole HP and 2 x one pole LP to make a 4 pole BP (band pass) then you can use the same old FIR based output tap mixing to generate all the different responses. It may not be so easy to do in a real circuit, but in software we're not bound by what is easy to build :) https://cytomic.com/files/dsp/cascade-all-to-all-responses.pdf Symmetry is one of the things. The other is the shape of the amplitude response. I'm personally not convinced by the -4dB dip prior to the resonance, although YMMV. At any rate it doesn't qualify as a "bread and butter" LP IMHO ;) With BP8 it's getting way worse. Incidentally, another way to come at more or less the same structure is raising the orders of LP and HP filters (by stacking identical 1-poles in series) in the transposed Sallen-Key (Fig.5.23 of the book). Since TSK is essentially a bandpass ladder with a special output mode, it's actually the same. Further ways (originating at lowpass ladder) to look at this can be found here: https://www.kvraudio.com/forum/viewtopic.php?p=6844369#p6844369 and here https://www.kvraudio.com/forum/viewtopic.php?p=6844470#p6844470 Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Book: The Art of VA Filter Design 2.1.0
On 01-Nov-18 15:18, pa...@synth.net wrote: Hmmm, 500 A4 pages would be rather heavy ;) I'd willingly pay for a copy. Quite pleased to hear that, thank you ;) Still, you could ask a copy shop to print and bind a copy for yourself (the book license allows it). I have been considering selling this book for money, but so far I don't really want to do that. One of the reasons, it'd be prohibitively difficult to release small updates such as this one. Best regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Book: The Art of VA Filter Design 2.1.0
On 31-Oct-18 18:19, Stefan Stenzel wrote: Vadim, I was more refering to the analog multimode filter based on the moog cascade I did some years ago, and found it amusing to find a warning against it. Ah, you mean the one at the beginning of Section 5.5? Well, that's an artifact of the older revision 1, where the ladder filter was introduced before the SVF (I still believe it's better didactically, unfortunately new material dependencies made me switch the order). The modal mixtures of the transistor ladder are asymmetric (HP is not symmetric to LP and has the resonance peak kind of "in the middle of its slope" and BP is not symmetric on its own). I felt that it might be confusing for a beginner if their first encounter with resonating HP and BP is with this kind of special-looking filters, hence the warning. With revision 2 this warning becomes less important, since the 2-pole LP and BP were discussed already before, but I still believe it's informative. After all, it doesn't say that these filters are bad, it says that they are special ;) Anyway, excellent writeup, Thank you! I'm glad my book is appreciated not only by newbies, but also by the industry experts. I wish I cuold have it printed as a proper book for more relaxed reading. Hmmm, 500 A4 pages would be rather heavy ;) Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Book: The Art of VA Filter Design 2.1.0
On 31-Oct-18 15:58, Stefan Stenzel wrote: Thank you very much, Sir! You're highly welcome, Sir! But why the warning about multimode lattice filters? In my case, this comes way too late! I'm not sure I'm fully following you... Or are you referring to this: New additions: - Generalized ladder filters You mean, why isn't this discussed in Chapter 5? Well, good question. But in the same sense, one could ask why generalized SVF doesn't come in Chapter 4. Chapter 8 is specifically concerned with building filters with arbitrary transfer functions of arbitrary orders, whereas Chapters 4 and 5 rather deal with structures commonly used in synths (more or less), and from this POV it belongs there. Also, had I discussed it in Chapter 5, it would have been difficult to derive it from the generalized SVF idea, which in my opinion is highly educative. Actually, are you by any chance aware of this structure being discussed elsewhere? Haven't encountered anything like that so far (not that it's difficult to derive ;) ), just wanted to build a nonlinear 2nd kind Butterworth filter of 4th order, so needed something like that ;) Best regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
[music-dsp] Book: The Art of VA Filter Design 2.1.0
Announcing a small update to the book https://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign_2.1.0.pdf New additions: - Generalized ladder filters - Elliptic filters of order 2^N - Steepness estimation of elliptic shelving filters Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] variations on exponential curves
On 01-Oct-18 13:58, Frank Sheeran wrote: For curves other than 0 and 1, I discover a delta that will work to the exact number of samples iteratively because I am too stupid to figure out an equation for delta. Werner is much better at math than I am! This is quite a smart way to work around the precision loss issues! Although I'm somewhat concerned about its reliability. I guess it can be proven that the final value is a monotonic function of delta, but possibly with large multipliers the output value step (for the smallest change of delta) will be quite large, so the search will not fully converge. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] variations on exponential curves
On 01-Oct-18 14:12, Vadim Zavalishin wrote: In principle IIRC the same rule applies for multiplier < 1, but there the losses are not too large. This also manifests at multiplier = 1 by having the "best offset" so that the curve's middle is at zero. Sorry, I meant to say that for multiplier < 1 you need the opposite rule, the curve should end at zero. Therefore at mult = 1 you position the curve halfway ;) Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] variations on exponential curves
On 01-Oct-18 13:52, Frank Sheeran wrote: Indeed, that's a simple parametric, but for generating envelopes we have the freedom to depend on the previous sample's output. So, while an exponential curve parametric-style requires a pow(), the iterative solution is simply current = previous * multiplier. Adding a range of curves can be done by adding a delta, as Andre/Werner and I have independently discovered (along with probably many others). And "current = previous * multiplier + delta" is going to be fewer calculations than a parametric formula such as yours. So I suggest the Andre/Werner/my method seems faster for the specific application of envelopes, as well as offering true exponential curves. With multiplier values >> 1 there can be noticeable incremental precision losses. They can be reduced by offsetting the whole curve so that its starting position is zero (which means that that the "output" value is current + offset). In principle IIRC the same rule applies for multiplier < 1, but there the losses are not too large. This also manifests at multiplier = 1 by having the "best offset" so that the curve's middle is at zero. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] What is resonance?
On 20-Jul-18 18:13, Mehdi Touzani wrote: So... how do you do a resonance in a lowpass circuit? :-) not the math, not the code, just the architecture. There are many different ways to create resonance in a lowpass circuit (esp. if the order is larger than 2). The higher is the order of the filter, the more different answers there are. Making a feedback loop around a lowpass chain is one way, but AFAIK it works perfectly (or close to that) only for the 4th order filter (the so called Moog ladder). I'm not aware of any standard generic structure (or even a transfer function to begin with) which could be referred to as a generic Nth order resonating filter. Recently I tried to propose one way of generalizing the 2nd order resonance to an arbitrary order by what I called "Butterworth filters of the 2nd kind", but this involves just the transfer function, whereas you still have lots of freedom in the implementation structure. You could look into the latest revision of my book for more details (where I also explain the problems with the lowpass feedback). Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Book: The Art of VA Filter Design 2.0.0alpha
On 21-Jun-18 00:55, list_em...@icloud.com wrote: Thank you for this work! You're welcome! May I make a suggestion—do not use an acronym in the title. This might not be obscure to you but it might be obscure to someone who would otherwise benefit from your book. This might be a good idea, although, on the other hand, changing the title, under which the book is already known, might be not necessarily the best thing to do. I'll give it a thought though, thanks! Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
[music-dsp] Book: The Art of VA Filter Design 2.0.0alpha
Hi everyone! As usual, I'm duplicating here the announcement on KVR, since (I assume) not everyone from this list is also present there. The Art of VA Filter Design has been updated to 2.0.0alpha. Freely available at this link: https://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign_2.0.0a.pdf Major highlights compared to the previous release: - different presentation of Sallen-Key filters - 8-pole ladders - detailed discussion of nonlinearities - "Butterworth filters of the 2nd kind" - different presentation of shelving filters, high-order generalized Butterworth and elliptic shelving - generalized Linkwitz-Riley crossovers - lots of theoretical stuff - last but not least: a neat formula for the frequency shifter's poles The book is a mixture of new research, common knowledge (presented from the POV of the author) and reinventing the wheel. I would be thankful for pointers to previous research, which I might not be aware of. Some of the new material is used in the soon to be released Reaktor Core macro library update, so it can be tried out (and looked into) directly there. The book is in the "alpha" state, some of the material had only surface checking and to an extent is a bit of a "work in progress". Best regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Elliptic filters coefficients
I don't know if it is possible to make the math behind elliptic filters
simpler. They really stand out by using somewhat exotic functions.
As for the online resource about filter basics unfortunately I can't
recommend any. Also IMHO the resource choice may be strongly affected by
your goals.
Regards,
Vadim
PS. If your goal is to design synth filters, I probably would have
recommended my book, but it requires some math background, and also
since you seem to be interested in elliptic filters, I'm not sure if
this is the area you're looking for.
On 02-Feb-18 12:37, Dario Sanfilippo wrote:
Thanks, Vadim.
I don't have a math background so it might take me longer than I wished
to obtain the coefficients that way, but it's probably time to learn it.
With that regard, would you have a particularly good online resource
that you'd suggest for pole-zero analysis and filter design?
Thanks to you too, Shannon.
Best,
Dario
On 1 February 2018 at 11:16, Vadim Zavalishin
<mailto:vadim.zavalis...@native-instruments.de>> wrote:
Hmm, the Wikipedia article on elliptic filters has a formula to
calculate the poles and further references the Wikipedia article on
elliptic rational functions which effectively contains the formula
for the zeros. Obtaining the coefficients from poles and zeros
should be straightforward.
Regards,
Vadim
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Reaktor Application Architect
Native Instruments GmbH
+49-30-611035-0
www.native-instruments.com
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Re: [music-dsp] Elliptic filters coefficients
Hmm, the Wikipedia article on elliptic filters has a formula to calculate the poles and further references the Wikipedia article on elliptic rational functions which effectively contains the formula for the zeros. Obtaining the coefficients from poles and zeros should be straightforward. Regards, Vadim On 01-Feb-18 12:00, Dario Sanfilippo wrote: Hello, everybody. I was wondering if you could please help me with elliptic filters. I had a look online and I couldn't find the equations to calculate the coefficients. Has any of you worked on that? Thanks, Dario ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] ± 45° Hilbert transformer using pair of IIR APFs
Funny that no one mentioned this https://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign_1.1.1.pdf Particularly, formula 7.43 Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Delays: sampling rate modulation vs. buffer size modulation
On 23-Mar-16 00:45, Matthias Puech wrote:
Does this mean for instance that if I provide a control over the
integral of D in 1/ I will get the exact same effect as in 2/?
I have been thinking about this question a while ago (in terms of tape
rather than BBD delay, but that's more or less the same). It seems that
you need to solve an integral equation, something like (latex notation)
\int_{t-T}^t v(\tau)d\tau = L
where
t = the current time moment
T = the delay time (the unknown to be found)
v(\tau) = tape speed
L = distance between the read and write heads
For an arbitrary v(t) this can be solved only numerically. For a
predefined v(t) this can be done analytically.
Regards,
Vadim
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Reaktor Application Architect
Native Instruments GmbH
+49-30-611035-0
www.native-instruments.com
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Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?
Okay, an updated idea. Represent the signal as a sum of time-shifted box functions of random amplitudes and durations. We assume that the sum is finite and then we can take the limit (if the values approach the infinity as the result, we can normalize them according to the length of the signal). Respectively the (complex) spectrum of such sum will be the sum of box function spectra which are randomly phase-rotated and randomly scaled/stretched in the frequency domain (according to their stretching in the time domain). The phase rotation can be assumed uniformly distributed. So we need to determine the distribution of the amplitudes and of the stretching of the box function spectra. Both of the latter can be found from the distribution of the box amplitudes and box lengths (under the assumption of uniform phase rotation distribution). The box amplitudes are uniformly distributed according to your specs. The distribution of box lengths must be IIRC one of the commonly known distributions, don't remember which one. On 06-Nov-15 11:06, Vadim Zavalishin wrote: On 06-Nov-15 11:03, Vadim Zavalishin wrote: Apologies if this question has already been answered, I didn't read the entire thread, just wanted to share the following idea off the top of my head FWIW. Oops, nevermind, I didn't realize that the SnH period is also random in the original question. -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?
On 06-Nov-15 11:03, Vadim Zavalishin wrote: Apologies if this question has already been answered, I didn't read the entire thread, just wanted to share the following idea off the top of my head FWIW. Oops, nevermind, I didn't realize that the SnH period is also random in the original question. -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?
Apologies if this question has already been answered, I didn't read the entire thread, just wanted to share the following idea off the top of my head FWIW. Consider a random PCM signal whose period is equal to the SnH period. This is the same as discrete-time noise and, if I'm not mistaken, given the random generator is ideal (uncorrelated) its PSD is simply flat everywhere. Now, in order to get the random SnH signal we need to convolve it with a box function. So, the remaining question is what's the effect of convolution on the PSD. Is it simply multiplication in the frequency domain or not? OTOH, if we are not talking of PSD, but rather of normal spectra, then we need to assume some time-domain windowing of the noise. The phases are going to be uniformly random (except for frequencies which are low, "compared to window length"). The amplitudes will be following the Gaussian distribution according to CLT. Assuming the window is large enough (and the signal is uncorrelated), I guess the standard deviations of the amplitudes for each frequency will be equal. Now, if we apply a convolution to this windowed signal, it's going to simply multiply the spectra of the signal and the window, and so will be the standard deviations. What has to be kept in mind though is that convolving a windowed signal is not exactly the same as windowing a convolved signal and this is going to distort the picture at lower frequencies (I guess). Regards, Vadim On 03-Nov-15 18:42, Ross Bencina wrote: Hi Everyone, Suppose that I generate a time series x[n] as follows: >>> P is a constant value between 0 and 1 At each time step n (n is an integer): r[n] = uniform_random(0, 1) x[n] = (r[n] <= P) ? uniform_random(-1, 1) : x[n-1] Where "(a) ? b : c" is the C ternary operator that takes on the value b if a is true, and c otherwise. <<< What would be a good way to derive a closed-form expression for the spectrum of x? (Assuming that the series is infinite.) I'm guessing that the answer is an integral over the spectra of shifted step functions, but I don't know how to deal with the random magnitude of each step, or the random onsets. Please assume that I barely know how to take the Fourier transform of a step function. Maybe the spectrum of a train of randomly spaced, random amplitude pulses is easier to model (i.e. w[n] = x[n] - x[n-1]). Either way, any hints would be appreciated. Thanks in advance, Ross. -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] List settings after the switch
- So, it seems both addresses (music-dsp@music and music-dsp@lists...) do actually work (so, apologies for a double mail) but with a 30 minute latency. Used to be less than 1 minute before (when the old list server was active). Maybe it's a local glitch on my mailserver, but that happened to 2 mails in a row (actually 3, counting the double mail). - The Reply button seems to work for the messages sent by myself (they go to the list, not to me) - The list web page that I meant is the old list page (the one found by google, if searching for the music dsp list). On the opposite, the new list page is not pointing to the old archives. Regards, Vadim On 10-Aug-15 10:46, Vadim Zavalishin wrote: Hi Douglas and all, it seems that after the switching of the list server there are a few issues, which I just noticed: - the "reply-to" field in the list mails is configured to the sender. So hitting "reply" no longer sends the answer to the list. I'm not sure whether this is the new standard, but I'm not sure whether it's so commonly used either. At least I'll need to learn to use the "Reply List" button. - the list web page is still pointing to the old archives only. it's seems not possible to find the new archives except by following the footer link in the list mails. I guess the addresses listed there for subscribing to the list do not work either. - the "reply list" button sends to "music-dsp@music.columbia.edu", which doesn't seem to work. the same email address is listed in the footer. I just have found the other address in the Trash folder in the test mail from Douglas, trying it now (I wonder why does it work for other people, who manage to write to the list?) Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
[music-dsp] List settings after the switch
Hi Douglas and all, it seems that after the switching of the list server there are a few issues, which I just noticed: - the "reply-to" field in the list mails is configured to the sender. So hitting "reply" no longer sends the answer to the list. I'm not sure whether this is the new standard, but I'm not sure whether it's so commonly used either. At least I'll need to learn to use the "Reply List" button. - the list web page is still pointing to the old archives only. it's seems not possible to find the new archives except by following the footer link in the list mails. I guess the addresses listed there for subscribing to the list do not work either. - the "reply list" button sends to "music-dsp@music.columbia.edu", which doesn't seem to work. the same email address is listed in the footer. I just have found the other address in the Trash folder in the test mail from Douglas, trying it now (I wonder why does it work for other people, who manage to write to the list?) Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] The Art of VA Filter Design book revision 1.1.0
Just realized that the following answer has never made its way through to the list. @Robert: I believe it has to do with your mail client settings, which override the "reply-to" field. So it's quite possible that more answers to your mails do not get to the list. Or is that on purpose? Hi Robert On 24-Jul-15 21:48, robert bristow-johnson wrote: in the 2nd-order analog filters, i might suggest replacing "2R" with 1/Q in all of your equations, text, and figures because Q is a notation and parameter much more commonly used and referred to in either the EE or audio/music-dsp contexts. I'm not such a big friend of the Q notation. My guess is that the Q parameter was introduced originally for something like radio tuning LC-circuits, where it makes perfect sense. For music 2-pole filters the problem is that Q changes from +inf to -inf during the transition into the selfoscillation region. OTOH, the R parameter is simply crossing the zero. Also see the footnote on page 84 of the rev 1.1.1. The R parameter also nicely maps to the pole position, being simply the cosine of the polar angle, while the cutoff is the radius. So the pole's coordinates are simply -w*cos R, +-w*sin R (for |R|<=1). in section 3.2, i would replace n0-1 with n0 (which means replacing n0 with n0+1 in the bottom limit of the summation). let t0 correspond directly with n0. On one hand makes sense. OTOH, using zero-based array indexing, like in C, n0 is intuitively understood as the first output sample. I agree, this is less conventional mathematically, but from a software developer's point of view this might be more intuitive. So, to an extent, I believe this is a matter of taste and intention. now even though it is ostensibly obvious on page 40, somewhere (and maybe i just missed it) you should be explicit in identifying the "trapezoidal integrator" with the "BLT integrator". you intimate that such is the case, but i can't see where you say so directly. p.40, directly under (3.5) "The substitution (3.5) is referred to as the bilinear transform, or shortly BLT. For that reason we can also refer to trapezoidal integrators as BLT integrators." Not good enough? section 3.9 is about pre-warping the cutoff frequency, which is of course oft treated in textbooks regarding the BLT. it turns out that any *single* frequency (for each degree of freedom or "knob") can be prewarped, not only or specifically the cutoff. Bottom of p.43 "Notice that it's possible to choose any other point for the prewarping, not necessarily the cuto ff point." etc in 2nd-order system, you have two independent degrees of freedom that can, in a BPF, be expressed as two frequencies (both left and right bandedges). you might want to consider pre-warping both, or alternatively, pre-warping the bandwidth defined by both bandedges. That's a good point. This approach is used in 7.9 but you're right, it should have been introduced in chapter 5. lastly, i know this was a little bit of a sore point before (i can't remember if it was you also that was involved with the little tiff i had with Andrew Simper), but as depicted on Fig. 3-18, any purported "zero-delay" feedback using this trapezoidal or BLT integrator does get "resolved" (as you put it) into a form where there truly is no zero-delay feedback. a "resolved" zero-delay feedback really isn't a zero-delay feedback at all. the paths that actually feedback come from the output end of a delay element. the structure in Fig 3-18 can be transposed into a simple 1st-order direct form that would be clear *not* having zero-delay feedback (but there is some zero-delay feedforward, which has never been a problem). The structure in 3.18 clearly doesn't have ZDF (although I don't think it can be made equivalent to any of direct forms without changing its topology and hence the time-varying behavior). That's the whole point of the illustration. However, once you get used to the ZDF, I'd say that it's probably much easier and more intuitive to stick to ZDF structures like 3.12 and understand the resolution implicitly (or actually even directly 2.2, you can notice that afterwards the book hardly uses any discrete-time diagrams). Particularly, when nonlinearities are introduced into the structure, thereby leaving you the freedom of choosing the numerical approach to treat them (post-resolution application, Newton-Raphson, analytical solution, "mystran's method" etc). i'll be looking this over more closely, but these are my first impressions. i hope you don't mind the review (that was not explicitly asked for). Would be highly appreciated. And thanks for the comments which you already made. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com ___ music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] The Art of VA Filter Design book revision 1.1.0
Released the promised bugfix http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign_1.1.1.pdf On 22-Jun-15 10:51, Vadim Zavalishin wrote: Didn't realize I was answering a personal rather than a list email, so I'm forwarding here the piece of information which was supposed to go to the list: While we are on the topic of the book, I have to mention that I found the bug in the Hilbert transformer cutoff formulas 7.42 and 7.43. Tried to merge odd and even orders into a more simple formula and introduced several mistakes. The necessary corrections are (if I didn't do another mistake again ;) ) - the sign in front of each occurence of sn must be flipped - x=(4n+2+(-1)^N)*K(k)/N - the stable poles are given by n -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
On 10-Jul-15 19:50, Charles Z Henry wrote: The more general conjecture for the math heads : If u is the solution of a differential equation with forcing function g and y = conv(u, v) Then, y is the solution of the same differential equation with forcing function h=conv(g,v) I haven't got a solid proof for that yet, but it looks pretty easy. How about the equation u''=-w*u+g where v is sinc and w is above the sampling frequency? -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
On 06-Jul-15 04:03, Sampo Syreeni wrote: On 2015-06-30, Vadim Zavalishin wrote: I would say the whole thread has been started mostly because of the exponential segments. How are they out of the picture? They are for *now* out, because I don't yet see how they could be bandlimited systematically within the BLEP framework. Didn't I describe this is my previous posts? But then evidently they can be bandlimited in all: just take a segment and bandlimit it. It's not going to be an easy math exercise, but it *is* going to be possible even within the distributional framework. I'd say even without one. A time-limited segment is in L2, isn't it? I don't think I'm good enough with integration to do that one myself. But you, Ethan and many others on this list probably are. Once you then have the analytic solution to that problem, I'm pretty sure you can tell from its manifest form whether the BLEP framework cut it. That would be a nice check, but I'm not sure I'd be able to derive an analytic closed-form expression for the related sum of the BLEPs which is what we need to compare against. But could you spot a mistake in my argument otherwise? Consider a piecewise-exponential signal being bandlimited by BLEP. That sort of implies an infinite sum of equal amplitude BLEPs, which probably can't converge. I think I have addressed exactly this convergence issue in my previous posts and in my paper. Furthermore, the convergence seems to be directly related to the bandlimitedness of the sine (see the paper). The same conditions hold for an exponential, hence my idea to define the "extended bandlimitedness" based on the BLEP convergence (or rather, the rolloff of the derivatives, which defines the BLEP convergence). Each of these exponentials can be represented as a sum of rectangular-windowed monomials (by windowing each term of the Taylor series separately). They can't: they are not finite sums, but infinite series, and I don't think we know how to handle such series right now. I meant "inifinite series of rectangular-windowed monomials". I'm not sure what specifically you are referring to by "we don't know how to handle them". We are just talking about pointwise convergence of this series. We can apply the BLEP method to bandlimit each of these monomials and then sum them up. We can handle each (actually sum of them) monomial. To finite order. But handling the whole series towards the exponential...not so much. Again, pointwise convergence is meant. If the sum converges then the obtained signal is bandlimited, right? If it does, yes. But I don't think it does. According to my paper, it does. Unless I did a mistake, the BLEP amplitudes roll off as 1/n, so if the derivatives (which are the BLEP gains) roll off exponentially decaying (which they do for a sine bandlimited to 1), the sum converges. Notice that this sufficient condition for the BLEP convergence is fulfilled if and only if the sine is bandlimited. I'm pretty sure you shouldn't be thinking about the bandlimited forms, now. The whole BLIT/BLEP theory hangs on the idea that you think about the continuous time, unlimited form first, and only then substitute -- in the very final step -- the corresponding bandlimited primitives. So it did, but what's wrong in doing the same for the monomial series? The sufficient convergence condition for the latter is that the derivatives of the exponent roll off sufficiently fast. But they don't, do they? Of course they do d^n exp(a*t) /dt^n = a^n * exp(a*t) so they roll off as a^n. The same for the sine. For a sine bandlimited to 1 we have a<1 and thus the BLEP sum converges. > When you snap an exponential back to zero, you necessarily snap back all of its derivatives. I'm not sure what you are referring to as "snapping". I mean, when you introduce a hard phase shift to a sine, you don't just modulate the waveform AM-wise. I do, if we consider the same in complex numbers. This is more or less what my paper is doing in the "ring modulation" approach. Especially when it gets bandlimited, the way you interpolate the waveform ain't gonna have just Diracs there, but Hilberts as well, and both of all orders... You lost me here a little bit. What's a Hilbert? 1/t? I thought it's the Fourier transform of a Heaviside. How is it a derivative of a Dirac? Furthermore, if we are talking in the spectral domain, we are going to have issues arising from the convergence of the infinite series in the time domain (you mentioned that the set of tempered distributions is not closed), that's why I specifically tried to stay in the time domain. That's the whole point: the bandlimitedness can be checked in the time domain, without even knowing the spectrum. Maybe th
Re: [music-dsp] Sampling theorem extension
On 30-Jun-15 00:43, Sampo Syreeni wrote:
And even if what we've been talking about above does go as far as I
(following Vadim) suggested, exponential segments are still out of
the picture for now.
I would say the whole thread has been started mostly because of the
exponential segments. How are they out of the picture? And if they are
out of the picture, then so must be the BLEP sines, because we don't
have a sufficiently rigorous framework to mathematically substantiate
the application of the BLEP method to the sine sync.
But I wonder if you can spot a mistake in the following (and if you do,
it probably should equally apply to the sine).
Consider a piecewise-exponential signal being bandlimited by BLEP. We
wish to know if we obtain a bandlimited signal in the result. Represent
the signal as a sum of rectangular-windowed exponentials. Each of these
exponentials can be represented as a sum of rectangular-windowed
monomials (by windowing each term of the Taylor series separately). We
can apply the BLEP method to bandlimit each of these monomials and then
sum them up. If the sum converges then the obtained signal is
bandlimited, right?
Now the sum of bandlimited rectangular-windowed monomials converges if
and only if the sum of their BLEP residuals converges. The sufficient
convergence condition for the latter is that the derivatives of the
exponent roll off sufficiently fast. We have seen exactly this for the
sine (in my paper), where the sufficient conditions for the BLEP
convergence is that the sine frequency is below Nyquist. Notice that the
Taylor series for exp is essentially the same as for the sine, therefore
they have the same rolloff speed. So, the exponent is "bandlimited" (in
the sense that the BLEP sum converges) under the same conditions as the
sine (the "frequency" must be below Nyquist).
On 29-Jun-15 21:15, Sampo Syreeni wrote:
I'm still going to have to let this one lie for awhile, because I
don't think it's what Schwarz's theorem actually says. Or that of
Hörmander.
Well, that's what Wikipedia says and a number of other sources. A signal
is bandlimited to A if and only if it's entire, its imaginary part is of
exponential type A (grows as exp(A*Im|x|) and otherwise has a polynomial
growth speed (or so I understood the statement, please correct me if I'm
wrong).
This is where the definition of "bandlimited" can be adjusted. The
signals which do not have spectrum are considered non-bandlimited,
whereas we can say that they are neither nor ("we don't know"). And I
was proposing an extended definition, which more or less seems to agree
with the usual one for all the signals which have spectra.
But in any case tell me, does what I was talking about seem like
your intuition? What do you think is the part which needs the most
work still?
It's pretty close in the intuitive reasoning to what I have been
thinking. Except that I would like to take this further to
non-polynomial entire functions (like the sine), and those which cannot
be handled by the tempered distribution framework (exponential), but
still are of practical importance.
--
Vadim Zavalishin
Reaktor Application Architect | R&D
Native Instruments GmbH
+49-30-611035-0
www.native-instruments.com
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Re: [music-dsp] Sampling theorem extension
On 24-Jun-15 21:30, Ethan Duni wrote: Could you expand a bit on exactly what it means to apply the BLEP method to the discontinuities? I have a general grasp of the basic idea but I'm a bit fuzzy on exactly what this means in practice. If you're getting a truly band limited signal, then isn't the result infinite in time extent? In which case how do you use this for dynamic synthesis in practice? If the idea is to stitch together these BLEP'd segments to represent, say, a hard-synced sawtooth or something, then don't you end up needing huge latency? By integrating the Dirac delta we obtain a Heaviside step function (a discontinuity of the 0th order). Integrating again we obtain a discontinuity of the 1st order and so on. The bandlimited version of the 0th order discontinuity is the integral sine Si(x). The bandlimited versions of discontinuities of higher orders are integrals of Si(x), which have analytical expressions via Si(x). The BLEP method replaces a discontinuity of each derivative by its respective bandlimited version. More detail can be found e.g. here http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/SineSync.pdf In practice the BLEPs need to be timelimited by windowing. But neither can we compute an infinite sum of those at a single point anyway (except in special cases), which is another tradeoff. As to the latency, practical window sizes have order of magnitude of a few samples which is a quite acceptable. -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
On 24-Jun-15 15:31, Sampo Syreeni wrote: Certainly any signal with compact support isn't bandlimited. That's the simplest form of the uncertainty principle. But even if you take a strictly bandlimited "window" function with rapid falloff (a bandlimited square/flattop convolved with itself a couple of times comes to mind), you can easily fit stuff under it which behaves nice as peaches with regard to derivative conditions, but manages to have arbitrarily high frequency content. I don't want to take bandlimited windows. I want to take a rectangular window. But then I can apply the BLEP method to the discontinuities in the function and the derivatives arising from this window. Now, do I get a bandlimited version in the result? If I apply the window to a polynomial (particularly a straight line, occuring in the sawtooth) or to a bandlimited sine and then "BLEP" the result, then I would expect to get a bandlimited signal in the result, right? Now, how about doing the same to an exponential? Say, the simplest form of phase modulation at low index, f(x)=sin(x+sin(x)/10). When you "window" that, the result has all of the properties you're asking for, including no discontinuities in any derivative and nice enough rolloff of them in modulus. So it obeys the Paley-Wiener-Schwartz conditions, and its Fourier transform extends into an entire function. But the resulting function still contains infinitely high frequencies, and so can't be sampled losslessly at any finite rate. Upon a first attempt I failed to estimate the growth of derivatives of an FM sine analytically. But numerical checks of the first few derivatives were suggesting that the derivatives are not rolling off fast enough. So I would expect that this function doesn't satisfy the PWS conditions (exponential growth along the imaginary axis). Furthermore, if it did satisfy the PWS conditions, this would have meant that the signal is bandlimited (according to the PWS theorem itself). Don't get me wrong, I'm not trying to rain on your parade. I'm pretty impressed that someone is willing to take the time to go back into the fundamentals, and I too would like to see stuff such as PM properly bandwidth limited. I don't think that the BLEP method is capable of bandlimiting an FM sine. But it might be able to bandlimit an FM sawtooth, even if FM is exponential. But I still don't see how you're going to get there starting with derivative conditions. To me they seem incommeasurate with what you're trying to achieve. The derivative rolloff is exactly what is defining the convergence of the sum of the BLEPs (one BLEP per derivative). More specifically, it is a sufficient condition for the convergence of the BLEPs. So, there seems to be a strong correspondence between the convergence of the BLEPs and the bandlimitedness of the "base" signal. -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
On 22-Jun-15 21:59, Sampo Syreeni wrote: On 2015-06-22, Vadim Zavalishin wrote: After some googling I rediscovered (I think I already found out it one year ago and forgot) the Paley-Wiener-Schwartz theorem for tempered distributions, which is closely related to what I was aiming at. It'll you land right back at the extended sampling theorem I told about, above. Exactly (if by "extended sampling theorem" you mean the sampling theorem for tempered distributions). And now, by dropping the polynomial growth on the real axis restriction in PWS, I can handle any analytic signal. And those which are not analytic are not bandlimited anyway. So why fret about the complex extensions? I'm not sure which specific meaning of the word "complex" you imply here. But the main motivation for the whole stuff is applying the BLEP method to frequency-modulated sawtooth and triangle, where the FM is either done in the exponential scale and/or the oscillator is self-modulated. In this case you get exponential segments (and more complex shapes if self-modulation is done in the exp scale I believe). This also should cover the question of applicability of BLEP to arbitrary signal shapes more or less. It's just that you don't need any of that machinery in order to deal with that mode of synthesis, and you can easily see from the distributional theory that you can't do any better. It seems I can do better. Because my question is not whether an infinitely-long signal, which doesn't even have Fourier transform, is bandlimited. My question is whether a time-limited version of that signal is "bandlimited except exactly for the discontinuities arising from the time-limiting". -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] The Art of VA Filter Design book revision 1.1.0
Didn't realize I was answering a personal rather than a list email, so I'm forwarding here the piece of information which was supposed to go to the list: While we are on the topic of the book, I have to mention that I found the bug in the Hilbert transformer cutoff formulas 7.42 and 7.43. Tried to merge odd and even orders into a more simple formula and introduced several mistakes. The necessary corrections are (if I didn't do another mistake again ;) ) - the sign in front of each occurence of sn must be flipped - x=(4n+2+(-1)^N)*K(k)/N - the stable poles are given by nhttp://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
BLEP bandlimiting to the discontinuities of y and its derivatives, obtaining (if the ifninite sum of BLEPs converges) some other signal y'. The signal x is called bandlimited if for any rectangular window w(t), the signal y' exists (the BLEPs converge) and y'=BL[y]. This definition is well-specified and directly maps to the goals of the BLEP approach. The conjectures are - for the signals which are in L_2 the definition is equivalent to the usual definition of bandlimitedness. - if y' exists (BLEPs converge), then y'=BL[y] If the BLEP convergence is only given within some interval of the time axis (don't know if such cases can exist), then we can speak of signals "bandlimited on an interval". -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
On 12-Jun-15 12:54, Andreas Tell wrote: I think it’s not hard to prove that there is no consistent generalisation of the Fourier transform or regularisation method that would allow plain exponentials. Take a look at the representation of the time derivative operator in both time domain, d/dt, and frequency domain, i*omega. The one-dimensional eigensubspaces of i*omega are spanned by the eigenvectors delta(omega-omega0) with the associated eigenvalues i*omega0. That means all eigenvalues are necessarily imaginary, with exception of omega0=0. On the other hand, exp(t) is an eigenvector of d/dt with eigenvalue 1, which is not part of the spectrum of the frequency domain representation. This means, there is no analytic continuation from other transforms, no regularisation or transform in a weaker distributional sense. On one hand cos(omega0*t) is delta(omega-omega0)+delta(omega+omega0) in the frequency domain (some constant coefficients possibly omitted). On the other hand, its Taylor series expansion in time domain corresponds to an infinite sum of derivatives of delta(omega). So an infinite sum delta^(n)(omega) (which are zero everywhere except at the origin) must converge to delta(omega-omega0)+delta(omega+omega0), correct? ;) This is just to illustrate that the eigenspace reasoning might not work for infinite sums. And I don't know the sufficient condition for it to work (and this condition wouldn't hold here anyway, probably). Or is there any mistake in the above? Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
On 11-Jun-15 19:58, Sampo Syreeni wrote: On 2015-06-11, vadim.zavalishin wrote: Not really, if the windowing is done right. The DC offsets have more to do with the following integration step. I'm not sure which integration step you are referring to. The typical framework starts with BLITs, implemented as interpolated wavetable lookup, and then goes via a discrete time summation to derive BLEPs. Right? I prefer analytical expressions for BLEPs of 0 and higher orders :) So the main problem tends to be with the summation, because it's a (borderline) unstable operation. I don't think so. The analytical expressions give beautiful answers without any ill-conditioning. So we don't know, if exp is bandlimited or not. This brings us back to my idea to try to extend the definition of "bandlimitedness", by replacing the usage of Fourier transform by the usage of a sequence of windowed sinc convolutions. The trouble is that once you go with such a local description, you start to introduce elements of shift-variance. How's that? This condition (transparency of the convolution of the original signal with sinc in continuous time domain) is equivalent to the normal definition of bandlimitedness via the Fourier transform, as long as Fourier transform exists. The thing is, by understanding the convolution integral in the generalized Cesaro sense (or just ignoring the 0th and higher-order "DC offsets" arising in this convolution) we might attempt to extend the class of applicable signals. This seems relatively straightforward for polynomials. As the next step we can attempt to use polynomials of infinite order, particularly the Taylor expansions, where the BLEP conversion question will arise. The answer to the latter might be given by the rolloff speed of the Taylor series terms (derivative rolloff). Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
On 11-Jun-15 11:00, Sampo Syreeni wrote: I don't know how useful the resulting Fourier transforms would be to the original poster, though: their structure is weird to say the least. Under the Fourier transform polynomials map to linear combinations of the derivatives of various orders of the delta distribution, and their spectrum has as its support the single point x=0. So they can be considered "kind of" bandlimited, although as I noted in my other post, it seems to result in DC offsets in their restored versions, if sinc is windowed. It probably can be shown that in the context of BLEP these DC offsets will cancel each other (possibly under some additional restrictions). So, this seems to agree with my previous guesses and ideas. You also mentioned (or I understood you so) that the exp(at) (a - real, t - from -infty to +infty) is not bandlimited (whereas my conjecture, based on the derivative rolloff speed, was that it's bandlimited if a is below the Nyquist). Could you tell us how does its spectrum look like? Thanks, Vadim -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
or the BLEP sum to converge is one and the same and has to do with the rolloff speed of the function's derivatives as the derivative order increases. -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Sampling theorem extension
On 09-Jun-15 22:08, robert bristow-johnson wrote:
a Nth order polynomial, f(x), driven by an x(t) that is bandlimited to B
will be bandlimited to N*B. if you oversample by a ratio of at least
(N+1)/2, none of the folded images (which we call "aliases") will reach
the original passband and can be filtered out with an LPF (at the high
sampling rate) before downsampling to the original rate. with 4x
oversampling, you can do a 7th-order polynomial and avoid non-harmonic
aliased components.
We are not talking about signals being fed through the polynomials. We
are talking about the polynomials as the signals.
I'm failing to see how Euler equation can relate exponentials of a real
argument to sinusoids of a real argument? Any hints here?
let f(x) be defined to be f(x) = e^(j*x)/(cos(x) + j*sin(x))
> .
I'm failing to see how Euler equation can relate exponentials of a *real
argument* to sinusoids of a *real argument*
I hope we are talking about
one and the same real exponential exp(at) on (-infty,+infty) and not
about exp(-at) on [0,+infty) or exp(|a|t).
oh, (assuming you meant e^(-|a*t|)), them's are in the textbooks.
Did I correctly understand you? The Fourier transform of exp(at) where a
and t are real and t is from -infty to +infty is in the textbooks? Any
hints how it looks like?
Yes, this is what I was referring to. Currently I'm interested in the
class of functions which are representable as a sum of a real function,
which, if analytically extended to the complex plane, is entire and
isolated derivative discontinuity functions (non-bandlimited versions of
BLEPs BLAMPs etc).
i think, if you allow for dirac impulses (or an immeasureably
indistinguishable approximation of width 10^(-44) second), any finite
and virtually bandlimited function will do. if you insist on being
strict with your mathematics, i can't help you anymore (it's been more
than 3 decades since i cracked open any Real Analysis or Complex
Variables or Functional Analysis textbook)
The problem currently is not the impulses, but the entire (complex
analytical) part of the signal.
BTW, i am no longer much enamoured with BLIT and the descendents of
BLIT.
I'm not sure how BLEP is a descendant of BLIT
Because, if the continuous part is bandlimited, then we have "just" to
replace the discontinuities by their bandlimited versions (the essence
of the BLEP approach) and the remaining question is only: if there are
infinitely many discontinuities at a given point, whether the sum of
their bandlimited versions will converge.
they don't. imagine a perfect brickwall filter with sinc(t) as its
impulse response. now drive the sonuvabitch with
{ (-1)^n n>=0
x[n] = {
{ -(-1)^n n<0
which is x[n] = -1, +1, -1, +1, +1, -1, +1, -1,
^
|
|
x[0]
and see what you get. it ain't BIBO.
Interesting observation. I might need to think a little bit more about
this :)
However I'm not sure how this is related to the convergence of the BLEPs
in the context which we are talking about.
Regards,
Vadim
--
Vadim Zavalishin
Reaktor Application Architect | R&D
Native Instruments GmbH
+49-30-611035-0
www.native-instruments.com
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Re: [music-dsp] Sampling theorem extension
On 09-Jun-15 19:23, Ethan Duni wrote: Could you give a little bit more of a clarification here? So the finite-order polynomials are not bandlimited, except the DC? Any hints to what their spectra look like? How a bandlimited polynomial would look like? Any hints how the spectrum of an exponential function looks like? How does a bandlimited exponential look like? I hope we are talking about one and the same real exponential exp(at) on (-infty,+infty) and not about exp(-at) on [0,+infty) or exp(|a|t). The Fourier transform does not exist for functions that blow up to +- infinity like that. I understood from Sampo Syreeni's answer, that Fourier transform does exist for those functions. And that's exactly the reason for me asking the above question. To do frequency domain analysis of those kinds of signals, you need to use the Laplace and/or Z transforms. Equivalently, you can think of doing a regular Fourier transform after applying a suitable exponential damping to the signal of interest. This will handle signals that blow up in one direction (like the exponential), but signals that blow up in both directions (like polynomials) remain problematic. Not good enough. If we're talking about unilateral Laplace transform, then it introduces a discontinuity at t=0, which immediately introduces further non-bandlimited partials into the spectrum. I'm not sure how you suppose to answer the question of the original signal being bandlimited in this case. With bilateral Laplace transform it's also complicated, because the damping doesn't work there, except possibly at one specific damping setting (for an exponent, where for polynomials it doesn't work at all), yielding a DC. I'm not fully sure, how to analytically extend this result to the entire complex plane and whether this will make sense in regards to the bandlimiting question. That said, I'm not sure why this is relevant? Seems like you aren't so much interested in complete exponential/polynomial functions over their entire domain, but rather windowed versions that are restricted to some small time region? I am specifically interested in the functions on the entire real axis. Further in my original email there is an explanation of the reasons. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
[music-dsp] Sampling theorem extension
functions, and integrate down to something which fulfils your condition yet will fail any normal sampling theory under the assumption of shift-invariance. If you don't have such a limit, then you're essentially already back to the theory of Schwartz spaces, which are used in the construction of the topology of the space of tempered distributions I mentioned above. See the above statement about the entire function. I just didn't mention this in the context of the other thread, trying to be brief. Anyway, here is my conjecture. The signals in our class of interest are a sum of two parts: - the "continuous part" a real function of real argument which is simultaneously entire in the complex plane. - the "discontinuous part" which is a sum of "non-bandlimited BLEPS (0th order), BLAMPS (1st order bleps) and higher-order bleps", where the discontinuity points are isolated but are allowed to have infinite "multiplicity" (that is at a single isolated point there may be discontinuities in all the derivatives). We are interested in: - whether the continuous part of our signal is bandlimited? - what is the rolloff speed of the derivative discontinuity amplitudes (as the order of the discontinuity grows) at each multiple-discontinuity point? Because, if the continuous part is bandlimited, then we have "just" to replace the discontinuities by their bandlimited versions (the essence of the BLEP approach) and the remaining question is only: if there are infinitely many discontinuities at a given point, whether the sum of their bandlimited versions will converge. The convergence of BLEPs is defined by the rolloff speed of the derivatives. My conjecture is that so is the bandlimitedness of the entire function, and that the rolloff speed requirement is exactly the same for both conditions! If this conjecture is true, this should automatically imply that all polynomials are bandlimited, since all their higher-order derivatives are zeros. Here is the older thread where I was asking the same question: http://music.columbia.edu/pipermail/music-dsp/2014-June/072679.html -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Did anybody here think about signal integrity
On 08-Jun-15 15:06, Theo Verelst wrote: Clearly, there's very little knowledge around the basic mathematical proofs underpinning a decent undergrad engineering course. Prisms understand fine what the Fourier transform is, and isn't. Maybe there's an interest in this: http://mathworld.wolfram.com/FourierTransformExponentialFunction.html . Clearly this is not the exponential signal which I was referring to. This is also a clear indication of the limitation of the sampling theorem I was referring to: since it's not possible to take Fourier transform of an exponential function, people refer to some other function as the "exponential function" in the context of the Fourier transform :) Anyway, since Theo expressed the wish not to change the direction of the thread, let's not stick to the question that I brought up. Although, if there is a renewed interest to discuss this aspect, I guess, creating a new thread could be an appropriate way to go. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Did anybody here think about signal integrity
The direct impact on the application can be e.g. using BLEPs (of 0th and higher orders) to antialias a sine hard sync or an exp-scale-modulated or self-modulated sawtooth (which produces exp segments), which seems to work but is lacking a firm theoretical foundation. In fact so does even the basic BLEP approach, since the function x(t)=at cannot be analyzed by the sampling theorem either. But I'm afraid I'm hijacking Theo's thread. Just wanted to point out another topic leading to the idea of the incompleteness of the sampling theorem. Although, if Theo doesn't mind, maybe we could further discuss this topic (or both topics simultaneously, since they seem to be related). Regards, Vadim On 08-Jun-15 10:54, STEFFAN DIEDRICHSEN wrote: IIRC, the discussion back then covered some topics like distortions created with polynomial functions, etc. Although DC isn’t a real problem in practical applications, there are many cases, which are hard to predict, if they cause aliasing. A good example is FM, which spectra can be predicted using Bessel functions, but who wants to do that? Or wave shaping using atan() or other transcendent functions. I think, there was a conclusion, that there are cases, which aren’t covered so well by theory, but the impact on the application can be overseen. Steffan On 08.06.2015|KW24, at 10:35, Victor Lazzarini wrote: Not sure I understand this sentence. As far as I know the FT is defined as an integral between -inf and +inf, so I am not quite sure how it cannot capture infinite-lenght sinusoidal signals. Maybe you meant something else? (I am not being difficult, just trying to understand what you are trying to say). Dr Victor Lazzarini Dean of Arts, Celtic Studies and Philosophy, Maynooth University, Maynooth, Co Kildare, Ireland Tel: 00 353 7086936 Fax: 00 353 1 7086952 On 8 Jun 2015, at 08:19, vadim.zavalishin mailto:vadim.zavalis...@native-instruments.de>> wrote: It might seem that such signals are unimportant, however even the infinite sinusoidal signals, including DC, cannot be treated by the sampling theorem, since the Dirac delta (which is considered as their Fourier transform) is not a function in a normal sense and strictly speaking Fourier transform doesn't exist for these signals. -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Did anybody here think about signal integrity
If you try to take the Fourier transform integral of a exp(j*omega_0*t), it will not converge in the sense, how an improper integral's convergence is usually understood. You will need to employ something like Cauchy principal value or Cesaro convergence to make it converge to zero at omega!=omega_0. At omega=omega_0 the integral diverges no matter in which sense you take it. So, strictly speaking, Fourier transform of a sine doesn't exist. An equivalent look to this from the inverse transform's side is that the spectrum of the sine is a Dirac delta function, which is not a function in the normal sense. So, none of the statements of the Fourier transform theory (including the sampling theorem, which assumes the existence of the Fourier transform), taken rigorously, seem to apply to the sinusoidal signals. Regards, Vadim On 08-Jun-15 10:35, Victor Lazzarini wrote: Not sure I understand this sentence. As far as I know the FT is defined as an integral between -inf and +inf, so I am not quite sure how it cannot capture infinite-lenght sinusoidal signals. Maybe you meant something else? (I am not being difficult, just trying to understand what you are trying to say). Dr Victor Lazzarini Dean of Arts, Celtic Studies and Philosophy, Maynooth University, Maynooth, Co Kildare, Ireland Tel: 00 353 7086936 Fax: 00 353 1 7086952 On 8 Jun 2015, at 08:19, vadim.zavalishin wrote: It might seem that such signals are unimportant, however even the infinite sinusoidal signals, including DC, cannot be treated by the sampling theorem, since the Dirac delta (which is considered as their Fourier transform) is not a function in a normal sense and strictly speaking Fourier transform doesn't exist for these signals. -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect | R&D Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Efficiently modulate filter coefficients without artifacts?
After writing the previous mail, I realized, that what I described in regards to mass-spring vs SVF was exactly the thing which I mentioned earlier: placing the (identical) cutoff gains before the integrators is equivalent to the time axis distortion. This might be seen as some kind of "proof" that such structures have the best time-varying performance in cases of cutoff modulation. Although, whether this is equivalent to the choice of the energy-based state variables in real-world physics systems is not fully clear to me yet. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Efficiently modulate filter coefficients without artifacts?
On 03-Feb-15 03:39, Andrew Simper wrote: I completely agree! I find it mentally easier to think of "energy stored" in each component rather than "state variables" even though they are the same. So for musical applications it is important that a change in the cutoff and resonance doesn't change (until you process the next sample) the energy stored in each capacitor / inductor / other energy storage component in your model. Direct form structures do not have this energy conservation property, they are only equivalent in the LTI case (linear time invariant - ie don't change your cutoff or resonance ever). Any method that tries to jiggle the states to preserve the energy would only be trying to do what already happens automatically with some of state space model, so I feel it is best to leave such forms for static filtering applications. I'm not sure whether the choice of the energy-based state variables is indeed the best one (would be nice to try to have some kind of formal proof of that), but at least it seems to me that it might be that the SVF has the optimal (in a way) choice of those. My consideration is the following. Imagine a generic 2nd order mechanical system. Something like a mass on a spring. The external excitation force is the input signal. The natural choice of state variables is the position and the velocity of the mass. We can look at it as at a multimode LP/BP/HP filter. Up to some scaling, the position is the lowpass output, the velocity is the bandpass output and the highpass can be obtained as a linear combination of LP, BP and the input. Since there are not that many possibilities to construct a 2nd order linear differential system, our system is equivalent to an SVF in the LTI sense. The time-varying behavior will depend on which specific coefficients of the 2nd order differential equations are modulated and on the choice of state variables. So, our state variables are the position and the velocity. Imagine our system has a high cutoff and we are feeding in a sufficiently high sinusoidal signal with the frequency below the cutoff. So the lowpass output (the position) is a similar sinusoid. At the zero-crossing time the velocity will be maximal. Suppose we suddenly lower the cutoff at this moment. Intuitively (I admit that this requires a more rigorous check), at a lower cutoff the velocity will not be changing so quickly any more. This means, the output signal of the system will significantly overshoot the previous output amplitude. In comparison, the state variables of the SVF are using the velocity divided by the cutoff. Which means a sudden reduction of the cutoff will proportionally reduce the velocity and the overshoot will not be that big anymore. In order to test your conjecture about the energy-based state variables, one would need to explicitly write down the mass-spring equation and compare the respective choices of state variables to those of SVF. Possibly, the energy-based state variables of the mass-spring system will be equivalent to the state variables of the SVF, which would then be a sign that your idea might be correct. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Efficiently modulate filter coefficients without artifacts?
On 04-Feb-15 00:25, robert bristow-johnson wrote: On 2/2/15 6:21 PM, Stefan Sullivan wrote: I actually found by playing around with a particular biquad problem that changing the topology of the filter had a greater impact on reducing artifacts than proving bibo stability. In fact, any linearly interpolated biquad coefficients between stable filters results in a stable filter, including with nonzero initial conditions ( http://dsp.stackexchange.com/a/11267/5321). i think so, too. because the stability depends on the value of a2 and ramping from one stable value of a2 to another stable value shouldn't be romping through unstable territory... I'm not sure what exactly you are referring to here, but your statement could evoke a common misconception. The "stable and unstable territories" are defined only for LTI systems (if you look at the corresponding proofs, they all assume the time-invariance property of the filter). That's why the works dealing with proving the time-invariant stability have to resort to other criteria, than mere pole positions. Rigorously speaking, there is no reason to believe that the same thing should apply to time-varying systems. Intuitively speaking, the change of parameters can work as an additional "unstabilizing factor", which is not taken into account by the LTI-specific "poles inside the unit circle" rule. As I mentioned earlier linked above proof is not convincing either, because it doesn't assume the infinite modulation of the coefficients. Sure, you can always treat the system as BIBO up to any given certain finite point in time, but from that point of view ANY linear system is BIBO. The point of the BIBO definition is to put a horizontal bound on the filter state growth, not to state that the filter state is finite at any finite time. but if there is vibrato connected to a filter's control parameters, i can see how a filter can go unstable an never settle down. This is exactly the point of the time-varying stability analysis. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Efficiently modulate filter coefficients without artifacts?
On 03-Feb-15 00:21, Stefan Sullivan wrote: ... In fact, any linearly interpolated biquad coefficients between stable filters results in a stable filter, including with nonzero initial conditions ( http://dsp.stackexchange.com/a/11267/5321). The trick is that the bounds may be different with nonzero initial conditions than with zero initial conditions. I took a glance at the proof and it doesn't look very convincing. If there's interest, we could further discuss the details. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Efficiently modulate filter coefficients without artifacts?
One should be careful not to mix up two different requirements: - time-varying stability of the filter - the minimization of modulation artifacts While both are probably closely related, there is no reason to believe that they are equivalent. My intuitive guess would be that the "absolutely best" (whatever that means) stability would occur (for 2-pole filters) for a filter based on the 2nd order resonating Jordan normal cell, which is effectively just implementing a decaying complex exponential: x[n+1] = A*(x[n]*cos(a)-y[n]*sin(a)) y[n+1] = A*(x[n]*sin(a)+y[n]*cos(a)) (the filter itself will be a state-space representation built around the above transition matrix). However, it's not even intuitively obvious if that structure would give you the minimal artifacts. In regards to the artifact minimization, I have only an intuitive suggestion. Let's look at the SVF structure in continuous time (e.g. Fig.5.1 on p.77 of http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign_1.0.3.pdf) and at the structure of the continuous-time integrator (the two untitled pictures on p.49 in the same text). It's intuitively clear, that the integrator structure, where the cutoff gain precedes the integration generates "less" artifacts, since the integrator is "smoothing out" the coefficient changes. This leads to the idea that in this case the lowpass output of the SVF would be quite reasonable in regards to the artifact minimization, since each of the cutoff coefficients is smoothed by an integrator and the resonance coefficient is smoothed by both of them. Similar considerations can be applied to the other modes, where it's clear that the HP output gets the unsmoothed artifacts from the resonance changes. If we want to build a mixture of LP/BP/HP modes rather than picking the outputs one by one, then, maybe it's possible to smooth the artifacts by using the transposed (MISO) form of the SVF, but I'm not usre. The thing with placing the cutoff before the integrator is pretty generic. It can be easily shown, that in this case the cutoff modulations can be equivalently represented as time dilation/compression (provided all integrators share the same cutoff), thus they don't affect the filter stability and their artifacts are exactly those of time axis warping. It would be reasonable to expect that if we then apply any state-variable preserving analog to digital transformation techniques (such as trapezoidal integration/TPT), the artifacts amount will be more or less the same. Similar reasoning can be applied to a continuous-time Jordan normal cell, which then can be converted to discrete time. One would then generally expect other discretization approaches, which do not preserve the topology and state variables, such as direct forms to have a way poorer performance in regards to the artifacts, unless, of course, it's an approach which specifically targets the artifact minimization in one or the other way. Regards, Vadim On 02-Feb-15 11:18, Ross Bencina wrote: Hello Robert, On 2/02/2015 10:10 AM, robert bristow-johnson wrote: also, i might add to the list, the good old-fashioned lattice (or ladder) filters. In the Laroche paper mentioned earlier [1] he shows that Coupled Form is BIBO stable and Normalized Ladder is stable only if coefficients are varied at most every other sample (which, if adhered to, should also be fine for the current discussion). The Lattice filter is *not* time-varying stable according to Laroche's analysis. I'd be curious to hear alternative views/discussion on that. [1] Laroche, J. (2007) “On the Stability of Time-Varying Recursive Filters,” J. Audio Eng. Soc., vol. 55, no. 6, pp. 460-471, June 2007. Cheers, Ross. -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] SVF and SKF with input mixing
I was referring specifically to the transposition of the linear continuous-time 1-pole lowpass filter (like a buffered RC circuit), where (off the top of my head) it seems that the only difference between the transposed and the original versions is the placement of the cutoff gain before or after the integrator, which can even be completely ignored, once we consider integrators-with-cutoffs as atomic elements. Along the same lines, the transposition of the transistor ladder, when treating the 1-poles as elementary blocks, seems to preserve the filter structure. Which, in case of the famous Antti's model means that we can preserve the nonlinearities as they are. Why I say "seems" is because I didn't try to verify this on paper, so I'm just reserving a possibility of a mistake ;) For the SVF you're right, the effect of the undampling nonlinearity is not obvious in the transposed version. Regards, Vadim On 06-Jan-15 14:57, STEFFAN DIEDRICHSEN wrote: Transposed filters have identical transfer functions, but differ in terms of rounding noise and coefficient quantization. In case of nonlinearities, it’s difficult. A typical non-linearity is the Diode circuitry to “un-damp” the filter, which can be seen as a voltage dependent voltage divider. In the original arrangement, like the SEM filter, it depends on the BP out, but if you transpose it, this output is lost. I’m not sure, if you get the same properties distortion wise after transposition. However, the analog input mixing filters will sound differently from a standard SVF, too. Steffan On 06.01.2015|KW2, at 14:40, Vadim Zavalishin wrote: (although I'm not sure, whether their transposed version is not identical to the original ;-) ). Things can get less straightforward, once nonlinearities are involved. -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] SVF and SKF with input mixing
The SVF transposition can be done in continuous-time domain (where the filter is basically two integrators in series, both feeding back to the input). Then, applying the trapezoidal integration/ZDF techniques we obtain a multi-input 2-pole SVF. Obviously, the same technique can be applied to any other linear multi-output filter, where in principle the transposition doesn't need to be applied on all levels of the filter. E.g. for a multimode transistor ladder we could handle the underlying 1-pole lowpasses as atomic blocks and not transpose them internally (although I'm not sure, whether their transposed version is not identical to the original ;-) ). Things can get less straightforward, once nonlinearities are involved. Regards, Vadim On 06-Jan-15 14:30, STEFFAN DIEDRICHSEN wrote: Actually, it’s an interesting filter. BTW, if you transpose Chamberlin’s SVF, you get a similar filter with HP/BP/LP inputs and a common output: Out = HP + f * (BP + Z1) Z1 += BP - Out * q + f * (Z2 + LP - Out) Z2 += LP - Out f: frequency coefficient q: Q factor coefficient Out: output Z1, Z2: state variables HP, BP, LP: filter inputs HNY! Steffan On 05.01.2015|KW2, at 14:19, Andrew Simper wrote: Thanks to the ARP engineers for the original circuit and Sam HOSHUYAMA's great work for outlining the theory and designing a schematic for an input mixing SVF. Sam's articles- Theory: http://houshu.at.webry.info/200602/article_1.html Schematic: http://houshu.at.webry.info/201202/article_2.html I have taken Sam's design and written a technical paper on discretizing this form of the SVF. I also took the chance to update the SKF (Sallen Key Filter) paper to more explicitly deal with input mixing of different signals, here they are in as similar form as possible: http://cytomic.com/files/dsp/SvfInputMixing.pdf http://cytomic.com/files/dsp/SkfInputMixing.pdf As always all the technical papers I've done can be accessed from this page: -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Instant frequency recognition
I think it can be done simpler. Just extend the inverse Fourier transform in the same way how the bilateral Laplace transform extends the direct Fourier transform. Any mistake in that reasoning? Regards, Vadim On 02-Aug-14 20:10, colonel_h...@yahoo.com wrote: On Fri, 1 Aug 2014, Vadim Zavalishin wrote: My quick guess is that bandlimited does imply analytic in the complex analysis sense. 1st off, I am fairly sure it is true that a BL signal cannot be zero over an interval, so two non-zero BL signals cannot differ by zero over an interval, so a function with cetain values over any interval is unique, so the rest of this may be cruft... However, an audio signal is most often a real valued function of a real value or a complex valued function of a real value whos imaginary part happens to be zero (often almost interchangably to little ill effect.) So to get an analytic complex function you'd have to extend the function. A non-zero analytic can't have a zero imaginary part, so we'd need a ``new'' imaginary part and to extent the real and imaginary parts to a neighborhood of the real line. Off the cuff I think you might use the real values of f on the real axis as boundary conditions for the Cauchy-Reimann equations in a neighborhood of the real axis to solve for a non-zero imaginary part for f(z) which would then be analytic. This is /if/ BL is enough to show such a solution exists tehn you're done (which I do not claim is false. I just can't see a way to get there.) Ron -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Instant frequency recognition
Sorry, I meant Laplace transform of a timelimited signal. On 01-Aug-14 10:06, Vadim Zavalishin wrote: On 01-Aug-14 05:22, colonel_h...@yahoo.com wrote: On Fri, 18 Jul 2014, Sampo Syreeni wrote: Well, theoretically, all you have to know is that the signal is bandlimited. When that is the case, it's also analytic, which means that an arbitrarily short piece of it (the analog signal) will be enough to reconstruct all of it as a simple power series. I believe it is true than band limited implies C^infinity, but the function is not complex, so it's a different use of the term analytic than in complex analysis, My quick guess is that bandlimited does imply analytic in the complex analysis sense. This must be a dual of Laplace transform of a bandlimited signal being analytic (entire). Although I could be missing something here. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Instant frequency recognition
On 01-Aug-14 05:22, colonel_h...@yahoo.com wrote: On Fri, 18 Jul 2014, Sampo Syreeni wrote: Well, theoretically, all you have to know is that the signal is bandlimited. When that is the case, it's also analytic, which means that an arbitrarily short piece of it (the analog signal) will be enough to reconstruct all of it as a simple power series. I believe it is true than band limited implies C^infinity, but the function is not complex, so it's a different use of the term analytic than in complex analysis, My quick guess is that bandlimited does imply analytic in the complex analysis sense. This must be a dual of Laplace transform of a bandlimited signal being analytic (entire). Although I could be missing something here. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Instant frequency recognition
On 16-Jul-14 15:29, Olli Niemitalo wrote: Not sure if this is related, but there appears to be something called "chromatic derivatives": http://www.cse.unsw.edu.au/~ignjat/diff/ Seems pretty much related and going further in the same direction (alright, I just briefly glanced at chromatic derivatives). Anyway, it seems that for the discrete time signals the situation is somewhat different from what I described for continuous time in that there are no derivative discontinuities for discrete time signals. At the same time it's not possible to locally compute the derivatives of the discrete time signals, so the local Taylor expansion idea is not applicable anyway (the same applies to the the chromatic derivatives, I'd guess). However, instead, we could simply apply the inter-/extra-polation to the obtained sample points. The most intuitive would be applying Lagrange interpolation, which as we know, converges to the sinc interpolation. However (again, remember the BLEP discussion), any finite order polynomial contains only the generalized DC component. Not very useful for the frequency estimation. So, the question is, what kind of interpolation should we use? Sinc interpolation would be theoretically correct, but, remember, that this thread is not about "strictily theoretically correct" frequency recognition, but rather about some "more intuitive" version with the concept of "instant frequency". Maybe we could attempt exactly fitting a set of samples into a sum of sines of different frequencies? Each sine corresponding to 3 degrees of freedom. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Instant frequency recognition
On 16-Jul-14 12:31, Olli Niemitalo wrote: What does "O(B^N)" mean? -olli This is the so called "big O" notation. f^(N)(t)=O(B^N) means (for a fixed t) that there is K such that |f^(N)(t)|where f^(N) is the Nth derivative. Intuitively, "f^(N)(t) doesn't grow faster than B^N" Regards, Vadim On Thu, Jul 10, 2014 at 4:02 PM, Vadim Zavalishin wrote: Hi all, a recent question to the list regarding the frequency analysis and my recent posts concerning the BLEP led me to an idea, concerning the theoretical possibility of instant recognition of the signal spectrum. The idea is very raw, and possibly not new (if so, I'd appreciate any pointers). Just publishing it here for the sake of discussion/brainstorming/etc. For simplicity I'm considering only continuous time signals. Even here the idea is far from being ripe. In discrete time further complications will arise. According to the Fourier theory we need to know the entire signal from t=-inf to t=+inf in order to reconstruct its spectrum (even if we talk Fourier series rather than Fourier transform, by stating the periodicity of the signal we make it known at any t). OTOH, intuitively thinking, if I'm having just a windowed sine tone, the intuitive idea of its spectrum would be just the frequency of the underlying sine rather than the smeared peak arising from the Fourier transform of the windowed sine. This has been commonly the source of beginner's misconception in the frequency analysis, but I hope you can agree, that that misconception has reasonable foundations. Now, recall that in the recent BLEP discussion I conjectured the following alternative "definition" of bandlimited signals: an entire complex function is bandlimited (as a function of purely real argument t) if its derivatives at any chosen point are O(B^N) for some B, where B is the band limit. Thinking along the same lines, an entire function is fully defined by its derivatives at any given point and (therefore) so is its spectrum. So, we could reconstruct the signal just from its derivatives at one chosen point and apply Fourier transform to the reconstructed signal. In a more practical setting of a realtime input (the time is still continuous, though), we could work under an assumption of the signal being entire *until* proven otherwise. Particularly, if we get a mixture of several static sinusoidal signals, they all will be properly restored from an arbitrarily short fragment of the signal. Now suppose that instead of sinusoidal signals we get a sawtooth. In the beginning we detect just a linear segment. This is an entire function, but of a special class: its derivatives do not fall off smoothly as O(B^N), but stop immediately at the 2nd derivative. From the BLEP discussion we know, that so far this signal is just a generalized version of the DC offset, thus containing only a zero frequency partial. As the sawtooth transition comes we can detect the discontinuity in the signal, therefore dropping the assumption of an entire signal and use some other (yet undeveloped) approach for the short-time frequency detection. Any further thoughts? Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
[music-dsp] Instant frequency recognition
Hi all, a recent question to the list regarding the frequency analysis and my recent posts concerning the BLEP led me to an idea, concerning the theoretical possibility of instant recognition of the signal spectrum. The idea is very raw, and possibly not new (if so, I'd appreciate any pointers). Just publishing it here for the sake of discussion/brainstorming/etc. For simplicity I'm considering only continuous time signals. Even here the idea is far from being ripe. In discrete time further complications will arise. According to the Fourier theory we need to know the entire signal from t=-inf to t=+inf in order to reconstruct its spectrum (even if we talk Fourier series rather than Fourier transform, by stating the periodicity of the signal we make it known at any t). OTOH, intuitively thinking, if I'm having just a windowed sine tone, the intuitive idea of its spectrum would be just the frequency of the underlying sine rather than the smeared peak arising from the Fourier transform of the windowed sine. This has been commonly the source of beginner's misconception in the frequency analysis, but I hope you can agree, that that misconception has reasonable foundations. Now, recall that in the recent BLEP discussion I conjectured the following alternative "definition" of bandlimited signals: an entire complex function is bandlimited (as a function of purely real argument t) if its derivatives at any chosen point are O(B^N) for some B, where B is the band limit. Thinking along the same lines, an entire function is fully defined by its derivatives at any given point and (therefore) so is its spectrum. So, we could reconstruct the signal just from its derivatives at one chosen point and apply Fourier transform to the reconstructed signal. In a more practical setting of a realtime input (the time is still continuous, though), we could work under an assumption of the signal being entire *until* proven otherwise. Particularly, if we get a mixture of several static sinusoidal signals, they all will be properly restored from an arbitrarily short fragment of the signal. Now suppose that instead of sinusoidal signals we get a sawtooth. In the beginning we detect just a linear segment. This is an entire function, but of a special class: its derivatives do not fall off smoothly as O(B^N), but stop immediately at the 2nd derivative. From the BLEP discussion we know, that so far this signal is just a generalized version of the DC offset, thus containing only a zero frequency partial. As the sawtooth transition comes we can detect the discontinuity in the signal, therefore dropping the assumption of an entire signal and use some other (yet undeveloped) approach for the short-time frequency detection. Any further thoughts? Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
On 03-Jul-14 15:29, Theo Verelst wrote: * The "locality" of the proper resampling/reconstruction (sinc) funtion is very limited: the amplitude of a single sinc function, regarding a single sample diminishes only with 1/t Yes, but we can window it (and then use the Fourier theory to analyse the artifacts brought up by that windowing). I think you can get very decent quality with quite moderate window lengths. * FM isn't bandwidth limited AT ALL taken at the continuous/analog face value like in a modular synth. Talking DX7-style FM, yes. However, talking analog-style FM, while still being non-bandlimited, we can wonder if the entire non-bandlimited part of the spectrum is "contained in the discontinuities". This is one of the main motivations for the thread. * Ring modulation as a standard 4 quadrant multiplication is perfectly frequency limited with the notion that the input signals are. But its band limit is the sum of the band limits of the sources, which makes it not Nyquist-limited "by default". An implementation which wants to deal with arbitrary waveforms could just use 2x upsampling/downsampling to produce properly bandlimited ring modulation output. With specific knowledge about analog-style waveform inputs we could instead directly apply the BLEPs. * Natural E powers are NOT frequency limited according to the normal Fourier transform. Normal Fourier transform is not capable to do any statement regarding bandlimitedness of exp(a*t), since it doesn't exist. However, for a certain practical goal (generating bandlimited piecewise-exponential signals) we could try to come up with a different definition of "bandlimitedness" (you can argue the correctness of continuing to use the term "bandlimited" here, but that's a slightly different topic). Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
On 03-Jul-14 08:00, Nigel Redmon wrote: On Jul 2, 2014, at 1:12 AM, Vadim Zavalishin wrote: As for using the wavetables, BLIT, etc, they might provide superior performance (wavetables), total absence of inharmonic aliasing (BLIT) etc., but, AFAIK they tend to fail in extreme situations like heavy audio-rate FM, ring modulation etc. BLEP, OTOH, should still perform equally good. Ring modulation shouldn’t be part of that, because given an equivalent output of an oscillator by any method (say, sawtooth from a wavetable oscillator, and a saw from another method—in general, the same harmonic properties and output sample rate), if the ring modulation (which is “balanced”, or four-quadrant amplitude modulation) results in aliasing, it will result in aliasing for any of the oscillator types, because it only depends on the frequency content of the oscillator output, not how it got there. Ring modulation is clearly a part of that. If the input waveforms of a ring mod can be specified analytically (which is normally the case in a fixed-layout synth) you can consider the ring mod as an oscillator itself. That is, you analytically compute the non-bandlimited output of the ring mod in the continuous-time domain and then apply BLEPs to the discontinuities in the output waveform. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
On 03-Jul-14 04:37, robert bristow-johnson wrote: i think i understand what you're saying. BLIT is a form of granular synthesis where the BLI is the grain. to frequency-modulate a waveform generated from launching these BLI grains, we are modulating the spacing of the onset time for each grain. the grains themselves are not scrunched or stretched like the waveform that comes out of a wavetable by modulating the phase-increment. Actually, it's not sufficient to just modulate the starting times of the BLI grains. You have to ensure the proper shape of the oscillator waveform in between the transitions (like the ones of the sawtooth) and that requires modulation of the DC offset of the BLIT. Which may produce aliasing on its own (including but theoretically not limited to aliasing from the discontinuities of the DC). Anyway, instead of addressing the problem in the BLI domain, which requires subsequent integration and runtime re-expression of the modulation in terms of the BLI DC, I think it's way more straightforward to address it in the BLEP doman, where you explicitly generate the necessary waveform and *only* need to take care of the derivative discontinuities. You can do this as long as you can consider the waveform in between the transitions as bandlimited. This was the main reason I started this topic. Oh, and as a footnote. I stated that BLIT doesn't generate inharmonic aliasing. This clearly applies only to the case where you are not using grains to generate the BLIT, but generate the BLIT directly. If you use grains, then I see no difference to the BLEP case (where you need to window the BLEPs), except the (unnecessary IMHO) runtime digital integration step. Yet another thing. From my previous explanation regarding the bandlimited exponent, I was really tempted to make the following generalized conjecture: a signal is bandlimited if and only if it's derivatives at some chosen point are O(B^N), where B is the band limit. Obviously, this statement works in one direction (derivatives of bandlimited signal are O(B^N). As for the opposite direction this should be true only for some class of signals (as it clearly fails for signals with discontinuities of some order). I wonder if there is an intuitive definition of this class, such as "analytic" or "with infinite convergence radius of Taylor series" etc. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
A further interesting observation regarding the bandlimitedness of exp(a*t), which kind of confirms my previous conjecture. We are considering a "periodic exp", which is a sawtooth, whose segments are exponential rather than linear. Consider the amplitudes of "unit" aliasing residuals (residuals for the discontinuity functions obtained by successful integration of the Dirac delta). Bandlimited Dirac delta is sinc(pi t/T), where sinc(t)=sin(t)/t. Integrating successfully with respect to t we notice that the amplitudes of the unit residuals fall off as (T/pi)^N/N. Where (T/pi)^N is just obtained form a standard property of integration of a horizontally stretched function and 1/N is obtained from the biggest term of the formula for the Nth antiderivative of Si(t). The derivatives of exp(a*t) fall off as a^N. Thus, the amplitudes of the residuals needed for exp(a*t) discontinuity bandlimiting fall off as (a*T/pi)^N/N. Therefore, if a*Tthe residuals will converge and exp(a*t) can be considered bandlimited, otherwise not. Notice that the same considerations can be applied to sin(a*t), which fully coincides with the known condition for sin(a*t) being bandlimited: sin(2*pi*f*t) is bandlimited iff f<1/2T a=2*pi*f a*Thttp://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
Hi Theo On 01-Jul-14 16:36, Theo Verelst wrote: The example with the e-power still cannot serve as a "perfect" example, no matter if we sweep the proper boundary conditions for going from the Fourier integral to the decent s-integral with the network response being thought to start at t=0 under the rug, because, like I clearly stated, the e-power sequence, as perfect sample-set of a decaying a*E^(b-c*t) function IS NOT BANDWIDTH LIMITED. Failing to grap (as usual) some of the terminology used in your post (such as "network response"), I would still like to ask, whether you are talking about unilateral Laplace transform here (put differently, whether your exp(t) is zero for t<0)? Because, if that is the case, then (a) the signal is obviously non-bandlimited and (b) one could conjecture that all aliasing is coming from the transition at t=0, where you have discontinuities in all derivatives. In my original post I was referring to infinitely long exp(t). Although, using the "DC plus integration" approach, suggested in this thread, I'm wondering, if a periodic "sawtooth-like" exp(a*t) contains all its aliasing in the discontinuities (that is, if we bandlimit them one by one, whether we are getting a bandlimited signal in the limit). Maybe if a is small enough, the derivative discontinuities will decay sufficiently fast for that? Oh, and could you also give the link to the other thread you mentioned? Thanks Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
On 01-Jul-14 19:08, Ethan Duni wrote: This means that in principle "any" piecewise polynomial signal with bandlimited discontinuities of the signal and its derivatives is also band limited. Sorry if I'm missing something obvious, but what is a "bandlimited discontinuity"? Despite the elaborate answer already given to that question, I'd like to get an answer from a different point of view, where we stick to continous-time domain. By considering bandlimiting in the continuous-time domain, prior to sampling (kind of virtual ADC), we have a simpler (IMHO) framework: if the continuous-time signals are bandlimited, we can simply sample them to produce non-aliasing digital signal, without *explicitly* considering "fractional delay filters" etc. The result should be pretty much the same, just with using more intuitive and simpler concepts. YMMV. We can define a 0th order discontinuity as a value discontinuity in the signal. Like the sawtooth level jumping from +1 to -1 at the transition. We could also define the discontinuity function as being 0 for t<0 and 1 for t>0 (you can set it to 0.5 at t=0). Then e.g. a sawtooth signal can be represented as a sum of inifinitely long x(t)=t plus the sum of discontinuity functions scaled to the necessary amplitudes and positioned at each transition of the sawtooth. For a triangle we have a discontinuity in the 1st derivative, which we can refer to as the 1th order discontinuity. The respective discontinuity function can be defined as 0 for t<0 and t for t>=0. Respectively the triangle will be a sum of x(t)=t and 1st order discontinuity functions. Etc. Now, the statement which I'm aiming at is something like "all non-bandlimited part of the spectrum of a signal is contained in its discontinuities". Obviously, this is not completely right, so the question was, to which extent is it right. Now, in the cases, where the statement holds, in order to bandlimit the signal it is sufficient to bandlimit the discontinuities. As for the construction of bandlimited discontinuities, we can use the fact that the integration changes the amplitudes and phases of the signal's partials but doesn't generate new ones (if the ill-conditioning at DC is properly respected). In order to obtain a bandlimited 0th order discontinuity (bandlimited step, or BLEP), we notice that it is an integral of the Dirac delta function. So we take the bandlimited version of the Dirac delta, which is known to be the sinc function and integrate it, obtaining a so-called integral sine, or sine integral function Si(t). The DC of the result needs to be corrected, though, but it's obvious. To obtain the 1st order discontinuity we integrate Si(t) again (for which there is an analytical expression). And so on. The discontinuity functions can be pregenerated and stored in tables, approximated by polynomials, etc. Of course, being infinitely long, they require some windowing. In the generation of the waveforms it might be more practical instead of adding bandlimited discontinuities to the "continuous" signal, add the resuduals (the differences between bandlimited and nonbandlimited versions of the same discontinuities) to non-bandlimited signal, but that's just a math trick to slightly simplify the processing, not an essential part of the entire idea. So, everything is very simple, provided the underlying "continuous" signal can be considered bandlimited (which was the original question in the thread). One slight complication arises from the discontinuities being non-causal, which adds the latency to the oscillator. Eli Brandt, who (I believe) introduced the BLEP method was suggesting to use minimum-phase versions of those (which I believe exist only in discrete-time domain), but personally I'm not a big fan of those, and would rather have the latency in the oscillator. As for using the wavetables, BLIT, etc, they might provide superior performance (wavetables), total absence of inharmonic aliasing (BLIT) etc., but, AFAIK they tend to fail in extreme situations like heavy audio-rate FM, ring modulation etc. BLEP, OTOH, should still perform equally good. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
An interesting observation. Since (t+a)^2=t^2+2at+a^2 the lowpass filtering of t^2 with a symmetrically windowed sinc gives (sincw * (.+a)^2)(t)= (sincw * (.^2+2a.+a^2)(t)= (sincw * .^2)(t)+(sincw * 2a.)(t)+(sincw * a^2)(t)= (sincw * .^2)(t)+0+a^2 = (sincw * .^2)(t)+a^2 where * is the convolution operator and . is the function's argument placeholder. This means that the lowpass filtering of t^2 may add a DC offset of (sincw * .^2)(t) but otherwise doesn't modify the function. Thus, t^2 is still kind-of bandlimited. The same argument probably generalizes to higher order terms. For a non-symmetrical window you just get another DC term from the convolution with the second term of the sum. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
On 01-Jul-14 12:00, robert bristow-johnson wrote: On 7/1/14 4:17 AM, Vadim Zavalishin wrote: I belive that, contrarily to the BLIT method, BLxx typically integrates in the continuous time domain. I fail to see any reason why should we prefer discrete-time domain integration. i dunno. maybe to reprogram a capacitor requires desoldering it from the circuit. but reprogramming a discrete-time integrator is writing and compiling a different line of code. I'm not sure why do we need to integrate at runtime at all (if I get your point correctly). I thought, one of the elements of BLEP etc is that you integrate "offline" as a part of preparation of your algorithm. The continuous-time domain integration has the benefit of avoiding any spectral distortion in the hi freq area. Also it can be performed analytically. we might ask "how"? internal upsampling (it's still discrete time, but closer to the continuous-time domain)? Either internal upsampling (again, in the "offline" mode, so you can upsample 1000 times or more), or use the analytical expression for the integral of sinc. This means that in principle "any" piecewise polynomial signal with bandlimited discontinuities of the signal and its derivatives is also bandlimited. okay, so you upsample a bit and integrate analytically and you've captured your "x(t)=t" more perfectly. now what are you gonna do? output to a high-speed D/A converter? downsample and output to the D/A at the original sample rate? (the latter would be equivalent to BLxx.) Again, the intention is to be able to modulate the oscillator frequency, incl. audio-rate modulations (osc sync, pwm etc included as well). AFAIK, BLIT approach doesn't work too well here. So, I'm just trying to understand the boundaries of applicability of BLEP and its generalized flavors from a sufficiently rigorous theoretical standpoint, nothing more. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
On 01-Jul-14 10:17, Vadim Zavalishin wrote: This addresses my original motivation to a large extent: applying BLXX not only to waveforms of stable frequencies, but also to their modulated versions. Although, not completely. Particularly, self-FM sawtooth produces an exponential signal. I wonder, whether exponents (at least those which are slow enough) are bandlimited. After all a good part of the sine signals (which are kind of versions of exponentials) are bandlimited. As the exponents go, I believe, I have some kind of answer. As we are going to get an infinite number of discontinuities with self-FM saw, the question of bandlimitedness of the exponent is somewhat academic. However, we could consider low-order polynomial approximations of the exponential signals and bandlimit the respective discontinuities. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
On 30-Jun-14 18:44, Stefan Stenzel wrote:
The tools of BLXX are DC, digital integrators/filters and your BLXX signals that
are bandlimited by definition, no sampling and no nonlinear operation involved.
So as there is no possible source for aliasing, there is no aliasing.
Okay. So in principle, we could construct a BLXX-ed signal by simply
integrating DC and bandlimited impulses a sufficient number of times, if
necessary correcting the DC to zero along the way. Convincing enough. (A
small remark: I belive that, contrarily to the BLIT method, BLXX
typically integrates in the continuous time domain. I fail to see any
reason why should we prefer discrete-time domain integration. The
continuous-time domain integration has the benefit of avoiding any
spectral distortion in the hi freq area. Also it can be performed
analytically.) This means that in principle "any" piecewise polynomial
signal with bandlimited discontinuities of the signal and its
derivatives is also bandlimited.
This addresses my original motivation to a large extent: applying BLXX
not only to waveforms of stable frequencies, but also to their modulated
versions. Although, not completely. Particularly, self-FM sawtooth
produces an exponential signal. I wonder, whether exponents (at least
those which are slow enough) are bandlimited. After all a good part of
the sine signals (which are kind of versions of exponentials) are
bandlimited.
So, can we apply the above reasoning to Taylor series expansions
(constructing Taylor series by repeated integration of signals)?
Especially, if we consider only exponential segments, rather than
infinitely long exponentials, then we could apply the above integration
scheme an infinite number of times to arrive at the result. But (!) so
we could do for the sine signals. This would mean that *any* sine is
bandlimited. So, there must be some flaw in that reasoning.
Besides, while Stefan provided an almost convincing justification of the
BLXX by integration of DC and impulses ("almost" is because there is
this unanswered question of inifinite integration in the construction of
the Taylor series, which is somewhat bothering). However, it would still
be interesting to get a consistent look at the same problem from the
virtual ADC point of view, if only for the sake of understanding.
Regards,
Vadim
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Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
On 27-Jun-14 13:45, STEFFAN DIEDRICHSEN wrote: Can we consider x(t)=t^2 bandlimited? No, that’s a nonlinear operation , unlike the integration. The difference betwenn both operations is what happens with the step. Actually not, as pointed out by Stefan. In fact, you don't need the condition t>=0. Just notice that t^2/2 and t are in the differentiation/integration relationship. Not really. If you differentiate a constant, the result is zero. Since all differentiation and integraton is linear, only the spectrum is modified, no new content is generated, so band limits are preserved. At least on paper. ;-) Actually, even not on paper. The problem is that the transformation of the signal spectra by the integration is ill-conditioned at omega=0. Therefore you should be careful when integrating signals whose spectra are nonzero around DC. Particularly, the spectrum of x=const is already infinite at DC. This means we have to be careful with any transformations or conclusions regarding that spectrum, let alone applying the integration. It is exactly this issue which leads to the divergence of the ideal lowpass filtering (sinc-convolution) for x(t)=t^2, and limited convergence (only in Cauchy principal value sense) for x(t)=t. Furthermore, if the transformation of spectra by the integration could have been applied to x(t)=const, x(t)=t, x(t)=t^2 etc without any further thought, then *any* sinusoidal signal would have been bandlimited (or at least I believe so). Indeed, sin(a*t) could be expanded into Taylor series around t=0. The convergence radius of this series would be infinte, I believe (since sin(z) is analytical). The series also converges absolutely (follows from the convergence of exp(z)). It doesn't converge uniformly on (-inf,+inf), but I believe this is unnecessary in order to conclude that the infinte sum of bandlimited signals is also bandlimited. OTOH, if, rather than integrating x(t)=t and bandlimited steps separately, we integrate a bandlimited sawtooth signal, then the resulting parabolic waveform should be bandlimited (here the ill-conditioning of the integration doesn't apply, since the DC of the sawtooth is 0). Thus, the original question of the theoretical justification of BLEP antialiasing remains open. At least for the waveforms with nonlinear segments, such as x(t)=t^2. Not sure. From which domain do you look at the problem? Time-discrete or time continous? In the time-discrete domain, there’s no way to distinct non-bandlimited from limited. And in the other domain, you have no band limit. I was considering bandlimited signals in the continous time domain. The bandlimiting in this domain is the first step of theoretical ADC. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] On the theoretical foundations of BLEP, BLAMP etc
A related conjecture: a signal is bandlimited, if and only if the result of sampling-and-restoring this signal is invariant relatively to the subsample time-shifts. Wonder if this is true or not. Regards, Vadim On 27-Jun-14 11:18, Vadim Zavalishin wrote: Hi all, this is a question, which has been bothering me for a while: what are the (more-or-less) rigorous theorectial foundations of the BLEP approach. Didn't happen to see any (maybe I'm just missing some references). I mean that on a formal look, the statement that "all nonbandlimited signal is contained in the signal discontinuities" sounds intuitively reasonable, but is missing a formal explanation (and is also clearly false for arbitrary waveforms, just consider FM modulation of one sine by another). I have been trying to build one. We consider a sawtooth as a basic example. The sawtooth can be represented as an infinite signal x(t)=a*t plus the steps. If we bandlimit the steps then the resulting BLEP-antialiased sawtooth will be bandlimited if and only if the signal x(t)=a*t is bandlimited. So how can we check that x(t)=t is bandlimited. We cannot really take the Fourier transform, as the integral diverges. So we need to find some other way for the reasoning. One approach would be to notice that x(t)=const is bandlimited and that x(t)=t is an integral of that, thus it is also bandlimited. Not very convincing. Especially since the bandlimitedness of x(t)=const is also "somewhere on the edge", because its spectrum involves Dirac delta. A probably more practical approach would be to remember the reason for requiring the bandlimitedness: we want the signal to be exactly restored by the ADC/DAC transformation. So, how about the following statement: we consider a signal bandlimited, if the convolution with the (properly scaled and stretched) sinc function doesn't change the signal. For x(t)=const such convolution obviously doesn't change the signal, so it can be considered bandlimited. For x(t)=t the convolution integral already converges *only* in the Cauchy principal value sense (notice that we need to take the convolution only at t=0, as at all other points we can reduce the problem to the convolution at t=0 plus the convolution with x(t)=const and we already know that the latter is unchanged by the convolution). So, what does this principal value convergence mean in practice. In practice we are not going to use an infinite sinc in the ADC, rather a windowed version thereof. Apparently, for any *symmetrical* window, the convolution with such windowed sinc will also not change x(t)=t. However, what if the window is not symmetric (unlikely, but theoretically possible)? I'm not sure, how to answer that. However, we are still relatively good for signals such as sawtooth, pulse and triangle. But what about parabolic signal (integral of the sawtooth). This signal can be introduced into the family of "classic analog waveforms" because it can be considered as a "even and odd harmonics" version of the triangle. Can we consider x(t)=t^2 bandlimited? The convolution with sinc converges only in some generalized Cesaro sense here and the symmetric windowing doesn't help. Does this mean that BLEP is not really applicable to this signal? (In the sense that it will not fully suppress the aliasing) A similar question can be raised for analog FM. E.g. a sawtooth modulating a sawtooth, where you also get x(t)=x^2. Or a self-modulated sawtooth where you get exp(t). Can exp(t) be considered bandlimited? The above also raises the question of whether the convolution of sinc with Si(t) leaves Si(t) unchanged? (Which would be a check that Si(t) is indeed bandlimited, since the Fourier transform of Si(t) also diverges, if I'm not mistaken). In principle we could take the residual approach in our formalization and rather than considering Si(t) consider the difference between Si(t) and the nonbandlimited step. Fourier transform will clearly converge for this difference, but then how to show that this difference contains exactly the entire nonbandlimited part of the signal? Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
[music-dsp] On the theoretical foundations of BLEP, BLAMP etc
Hi all, this is a question, which has been bothering me for a while: what are the (more-or-less) rigorous theorectial foundations of the BLEP approach. Didn't happen to see any (maybe I'm just missing some references). I mean that on a formal look, the statement that "all nonbandlimited signal is contained in the signal discontinuities" sounds intuitively reasonable, but is missing a formal explanation (and is also clearly false for arbitrary waveforms, just consider FM modulation of one sine by another). I have been trying to build one. We consider a sawtooth as a basic example. The sawtooth can be represented as an infinite signal x(t)=a*t plus the steps. If we bandlimit the steps then the resulting BLEP-antialiased sawtooth will be bandlimited if and only if the signal x(t)=a*t is bandlimited. So how can we check that x(t)=t is bandlimited. We cannot really take the Fourier transform, as the integral diverges. So we need to find some other way for the reasoning. One approach would be to notice that x(t)=const is bandlimited and that x(t)=t is an integral of that, thus it is also bandlimited. Not very convincing. Especially since the bandlimitedness of x(t)=const is also "somewhere on the edge", because its spectrum involves Dirac delta. A probably more practical approach would be to remember the reason for requiring the bandlimitedness: we want the signal to be exactly restored by the ADC/DAC transformation. So, how about the following statement: we consider a signal bandlimited, if the convolution with the (properly scaled and stretched) sinc function doesn't change the signal. For x(t)=const such convolution obviously doesn't change the signal, so it can be considered bandlimited. For x(t)=t the convolution integral already converges *only* in the Cauchy principal value sense (notice that we need to take the convolution only at t=0, as at all other points we can reduce the problem to the convolution at t=0 plus the convolution with x(t)=const and we already know that the latter is unchanged by the convolution). So, what does this principal value convergence mean in practice. In practice we are not going to use an infinite sinc in the ADC, rather a windowed version thereof. Apparently, for any *symmetrical* window, the convolution with such windowed sinc will also not change x(t)=t. However, what if the window is not symmetric (unlikely, but theoretically possible)? I'm not sure, how to answer that. However, we are still relatively good for signals such as sawtooth, pulse and triangle. But what about parabolic signal (integral of the sawtooth). This signal can be introduced into the family of "classic analog waveforms" because it can be considered as a "even and odd harmonics" version of the triangle. Can we consider x(t)=t^2 bandlimited? The convolution with sinc converges only in some generalized Cesaro sense here and the symmetric windowing doesn't help. Does this mean that BLEP is not really applicable to this signal? (In the sense that it will not fully suppress the aliasing) A similar question can be raised for analog FM. E.g. a sawtooth modulating a sawtooth, where you also get x(t)=x^2. Or a self-modulated sawtooth where you get exp(t). Can exp(t) be considered bandlimited? The above also raises the question of whether the convolution of sinc with Si(t) leaves Si(t) unchanged? (Which would be a check that Si(t) is indeed bandlimited, since the Fourier transform of Si(t) also diverges, if I'm not mistaken). In principle we could take the residual approach in our formalization and rather than considering Si(t) consider the difference between Si(t) and the nonbandlimited step. Fourier transform will clearly converge for this difference, but then how to show that this difference contains exactly the entire nonbandlimited part of the signal? Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Frequency bounded DSP
I'm also not sure I understand the question, although from a slightly different angle. As long as the sum of the bandwidths of the modulator and the carrier is below Nyquist, you're good, right? So, in principle, you can do arbitrary amounts of AM/RM by simply keeping the Nyquist equal to double of your desired bandwidth and bandlimiting again after each AM/RM. So, this way you can implement more or less arbitrary envelopes (and, in particular, oscillator sync for arbitrary waveforms), if you bandlimit them in advance (unless I'm missing something). Regards, Vadim On 03-Jan-14 16:09, Wen Xue wrote: Why not just inverse-transform any band-limited spectrum? (or have I got the question wrong?) Now, can we do better, can we make, say, some form of "other" envelope that is still frequency limited ? T.V. -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] RMS calculation with IIR filter?
This works only in integer arithmetics. In floating point you will potentially have a drift, due to precision losses (although, off the top of my head I could think of a few workarounds to handle those). Regards, Vadim PS. I guess this is exactly what "IIR" was supposed to mean in the context of the question. RMS, being a nonlinear function, cannot be computed by a linear IIR. On 03-Jan-14 14:03, Robert Bielik wrote: If you have a history buffer you only need one addition + subtration + multiply per sample, regardless of length of RMS, so that method will always be faster than an IIR. Regards, /Rob Tebjan Halm skrev 2014-01-03 14:01: hello music-dsp, is there a simple IIR filter which calculates the standard 300ms RMS value for audio signals dependent on the sample rate? if so, is it faster than a moving sum? best, tebjan -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] R: R: Trapezoidal integrated optimised SVF v2
On 13-Nov-13 11:56, Marco Lo Monaco wrote: I personally don’t think that automatic systems (DK) will be the panacea of nonlinear modeling (even if everybody here is dreaming of a realtime spice). Very often only a human can see patterns in circuits and find shortcuts to simplify things. +1 Besides the shortcuts, only a human can judge the critical aspects of the analog model being discretized. Such as - how precise should the component models be (e.g. if Ebers-Moll transistor model is sufficient or not), where in principle this question should be answered for each component separately - whether the difference between parameter values of identically marked components is having any critical effect - whether the effect caused by a certain element of the model (e.g. a nonlinearity) is musically insignificant (so that the element may be dropped) - to which extent we can assume independence of different parts of the device (ignore the current leakage and other crosstalk) and so on. Perhaps, if in future we have computational powers several orders higher than the currently available ones, such automatic system would be more realistic, as we will be able to afford ridiculously precise and detailed analog component models as the basis of our discretization. But from my feeling it's still a long long way. And then, how important is being able to automatically convert from analog schematics to digital? I mean there has been some amount of brilliant engineering work to design those analog devices, but it's not happening much more. So, after we have modelled them all, we are not gonna need any further modelling. OTOH, the lessons we learned from attempting to model those things (and you learn more, if you do this "by hand" rather than by some automated toolkit) should form an invaluable basis for the development of future software. We can design *new* filters, effects, etc, which all are gonna have "that analog sound". For that purpose of new designs (rather than modelling the old stuff), I believe the *continuous-time* block-diagram based approaches are more useful than the differential equations, as they are offering a more intuitive view of the signal processing (YMMV). The discrete-time block-diagrams are not that intuitive, in my opinion, but then again, you don't need to use them, if you implicitly understand the discretized version of the same analog block-diagram. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 12-Nov-13 10:10, Dave Gamble wrote: So let me go out on a limb here: if you take some single precision code and up it to double, and things get WORSE then there is something very strange about your original code that merits investigation. It's very easy. As I mentioned in my other email, switching from float to double halves the number of available SIMD channels, which means you need to run your code twice as many times. On the other hand, in my experience, most of the DSP algorithms are quite tolerant to using 32-bit floats (DF filters being one exception). -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 12-Nov-13 10:01, Dave Gamble wrote: Because switching from double to float will bring extremely small performance gains in CPU cost, and potentially sizeable problems with numerical issues. I'd be very careful with statements like that. There are people with exactly the opposite experience. YMMV ;-) -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 12-Nov-13 09:53, Dave Gamble wrote: Absolutely! SSE2, which by all the stats I've seen is entirely ubiquitous now, is double precision, and has been since 2004, which is close enough to a decade for my taste. http://en.wikipedia.org/wiki/SSE2 Well, you get only half the number of available channels with SSE if you use doubles. If 2 channels are sufficient for you, then you might not care, of course. -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 12-Nov-13 09:53, Dave Gamble wrote: PS. "Time-varying performance" is another word. "Nonlinearities" is the third one. Not criticisms I'm at all familiar with, I'm afraid. Can you expand? As we are talking about inferiority of DF compared to ZDF, I just mentioned the other two, which are even way more prominent than the quantization issues, as they can't be addressed by switching to 64 bit floats (but they already have been mentioned multiple times in the scope of the present discussion). DF has very poor time-varying (modulated parameters) performance and is absolutely uncapable of properly hosting the nonlinearities present in the original analog prototype. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 12-Nov-13 09:40, Tim Blechmann wrote: One word: SIMD well, when benchmarking my performance code, about 2% of the CPU time is spent in vector code, while about 60% is spent in scalar filter code. Hi Tim I can't believe vector code is running 30 times faster than the scalar code :-D :-D :-D Seriously speaking, this ratio very much depends on the details of the software. It might as well be that you have no scalar filter code at all. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 12-Nov-13 09:05, Dave Gamble wrote: Actually, I'll go one further: In 2013, single precision is just time wasting. It's a pathological case for analysis, but it shouldn't represent real-world usage. I'm reminded of a conversation I had with my PhD supervisor 12 years ago, when showing him some source which caused him to remark "single precision? What is this? 1980?". One word: SIMD Regards, Vadim PS. "Time-varying performance" is another word. "Nonlinearities" is the third one. -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 11-Nov-13 17:33, Dave Gamble wrote: At some point, the process of using algebraic rearrangements [...] got dubbed the "delay-free" or "zero delay filters" movement. Hi Dave I think this is exactly the source of the confusion. As the distinctive feature of those filters were zero-delay feedback loops, the filters were called "delay-free feedback filters" or "zero delay feedback filters" (which was further shortened to "zdf filters" or "0df filters"). Then someone thought that "0df" stands for "zero-delay filter" rather than "zero-delay feedback" and there you are :D Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Time Varying BIBO Stability Analysis of Trapezoidal integrated optimised SVF v2
On 11-Nov-13 15:32, Ross Bencina wrote: That's why I was somewhat surprised that you simply managed to restrict the eigenvalues of the system matrix in some coordinates. To be clear: the eigenvalues of the transition matrix only cover time-invariant stability. The constraint for time-varying BIBO stability is that all transition matrices P satisfy ||TPT^-1|| < 1 where ||.|| is the spectral norm and T is some constant non-singular change of base matrix. Okay, for the time-varying case it seems to be the eigenvalues of (P^T)*P in the discrete-time case, which according to Wikipedia define the spectral norm (while in the continuous time we have the eigenvalues of P^T+P). I'm currently a little short of time to take a precise look at all the details. Still, in both cases we are talking about some uniform property of eigenvalues of a symmetric matrix. In the discrete time they need to be smaller than one to kind of make sure the next state vector is smaller than the previous one (I think). In the continuous time case they need to be negative to kind of make sure that the time derivative of the state vector's length is negative. The main reason I am suspicious is that Laroche does not even try to cook up a change of basis matrix, or to show when it might be achieved. It's kind of an orphan result in that paper that goes unused for showing BIBO stability. IIRC from briefly reading his paper, his sufficient criterion turned out to be not applicable for the DF filters (which by themselves also didn't seem to be time-variant BIBO-stable, IIRC), therefore he resorted to some other approaches. That (and my own SVF investigation) led me to consider this kind of criterion as a more or less useless one at that time. But I may be wrong, it was a while ago and only a brief look. Particularly suspicious is that your coordinate transformation matrix is "built for the smallest damping", while the more problematic case seems to occur "at the larger damping". I'm not sure I follow you here. Smallest damping means most resonance, where the system decays most slowly. Don't you think this would be where the greatest problems would arise? Because of the "shooting" effect I described earlier. I discovered it by a numerical simulation of the system. For the low resonance the state vector moves in an ellipse (for the "worst-case" signal I described). The orientation and the amount of stretching of the ellipse depends on the resonance (the lower the resonance the more the stretch). You can suddenly switch to a lower resonance while your state vector is pointing at such angle, that the respective position on the new ellipse is within the "increasing radius" area. This will cause the state vector to grow. Disclaimer: this all goes under the notice that I didn't double-check my results or may even have forgotten some important details or simply remember them wrong. I was posting them mostly because I thought they might be interesting and/or usable to some extent for you (and maybe others). In short, using change of basis matrix T: [1 f] [0 1] We have the time-varying BIBO stability constraint: 0 < f < 2, g > 0, f < k <= 2 f provides the bound on k from below. This is also the kind of the result which I would intuitively expect at the first thought. It's just contradicting the *unverified* results of my earlier research, that's why I expressed my suspiciousness. Hopefully, I'll find time to check your research in more detail. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 11-Nov-13 13:04, Theo Verelst wrote: Alright, simply put: the paradigm used to work with digital filters is at stake Funnily enough, it's a mathematically trivial fact that in the LTI case the 0df filters are mathematically equivalent to the DF BLT filters. So, the only "non-scientific" part there is about estimating the errors of time-varying and nonlinear effects. But then, I'm not so much aware (please correct me, if I'm wrong), if there are any psychoacoustically usable measurables developed until now, which help with those estimations. OTOH, the psychoacoustically perceivable error of the linear model is clearly estimatable by using the frequency response paradigm, but as I just said, in this respect 0df is fully equivalent to the DF BLT. So, it seems to me that it's not the paradigm, which is being put at stake, but rather only the methodology of digital filter design. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] R: Time Varying BIBO Stability Analysis of Trapezoidal integrated optimised SVF v2
Hi Marco On 11-Nov-13 11:26, Marco Lo Monaco wrote: I basically demonstrate what I already said in my previous posts. The standard state-space approach leads to identical results to your algorithm, I would say even without the trick of the TPT, because of course we are talking about an instantaneous _linear_ feedback. Of course they are all equivalent, except for some small detail, as e.g. the usage of canonical integrators (although maybe even that was known for long time for trapezoidal integration). Of course the main purpose of my analysis was to keep in mind that you will _always_ have to deal with an "implicit"/hidden inversion of a matrix A of the analog system (actually (I-A*h/2)) With the filters used in practice, the matrices typically turn out to be either simple or have quite regular structures. This often is given for granted in the 0df (TPT) approach, as you are just solving one linear feedback equation, instead of trying to invert a 5x5 matrix etc. Of course, it's mathematically equivalent, but is much simpler. Also, the division (the most expensive operation) which you have to perform while solving that equation is more or less the same division by a0 which you need to perform in the computation of the BLT-based discrete-time coefficients. So, computationally I think the 0df approach is comparable (even if slighly more expensive at times) to the transfer-function based DF filters, expecially at audio-rate modulations. Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Time Varying BIBO Stability Analysis of Trapezoidal integrated optimised SVF v2
Hi Ross,
since you opened this topic, I thought I'd try to share the intermediate
results my findings, as much as I can remember them (that was a few
years back). Most of them concern the continuous time case.
First note regarding the continuous time case is that cutoff modulations
do not affect the BIBO stability at all. More rigorously:
- if the cutoff modulation is done by varying the gains *in front*
(rather than behind) of *all* integrators in the system
- if the cutoff function w(t) is always positive
- if the system is BIBO stable for some cutoff function w(t)
then the system is also BIBO stable for any other positive cutoff function
Particularly, if a linear system is BIBO-stable in time-invariant case
(for the constant cutoff function), then it's also stable for varying
cutoff.
This is very easy to obtain from the state-space equation:
du/dt=w*F(u,x)
where u(t) is the state vector, x(t) is the input vector, w(t) is the
cutoff scalar function and F(u,x,t) is the nonlinear time-varying
version of A*u+B*x. Without reduction of generality we can assume w(t)=1
for the given stable case. Then, we simply rewrite the equation as
du/(w*dt)=F(u,x)
and substitute the time parameter:
d tau = w*dt
Now in "tau" time coordinates the modulated system is exactly the same
as the unmodulated one in the "t" coordinates.
The same doesn't seem to hold for the TPT discrete-time version, though.
In a more general case for *linear* continuous time, IIRC, we have a
sufficient (but it seems, not necessary) time-varying stability
criterion: all eigenvalues of the matrix A+A^T must be "uniformly
negative", that is they must be bounded by some negative number from
above. It is essential to require this uniform negativity, otherwise the
eigenvalues can get arbitrarily close to the self-oscillation case. This
condition is simply obtained from the fact that in the absence of the
input signal you want the absolute value of the state to decay with a
relative speed, which is uniformly less that 1. This will make sure,
that, whatever the bound of the input signal is, a large enough state
will decay sufficiently fast, to win over the input vector B(t)*x(t).
Indeed, ignoring the B*x term, we have
(d/dt) |u|^2=(d/dt)(u^T*u)=u'^T*u+u^T*u'=
(A*u)^T*u+u^T*(A*u)=u^T*A^T*u+u^T*A*u=
u^T*(A+A^T)*u<=|u|^2*max{lambda_i}
where lambda_i are the eigenvalues of A+A^T.
Now on the other hand
(d/dt) |u|^2=2*|u|*(d/dt)|u|
So
2*|u|*(d/dt)|u|<=|u|^2*max{lambda_i}
and
2*(d/dt)|u|<=|u|*max{lambda_i}
Obviously, you don't have to satisfy the condition in the original
state-space coordinates. Instead, you can satisfy it in any other
coordinates, which corresponds to using P^T*A*P instead of A for some
nonsingular matrix P.
Now I didn't manage to get this condition satisfied for the
continuous-time SVF. Reading your post, I admit, that I could have made
a mistake there, but FWIW... First, I discarded the consideration of
varying cutoff, as explained above and concentrated on the varying
damping. Not managing to find a matrix P, I constructed an input signal,
requiring the maximum possible growth of the state vector. The signal,
IIRC was either sgn(s_1) or -sgn(s_1), where s_1 is the first of the
state components (or it could have been s_2). Then I noticed that for
low damping the state vector is moving in almost a circle, while for
higher damping (but still with complex poles) is turns into an ellipse.
This was exactly the problem: "in principle" the circle is having a
bigger size, than the ellipse, but by switching the damping from low to
high you could "shoot" the state point into a much "higher orbit". Much
worse, in certain cases the system state can increase even in the full
absence of the input signal!!! However, IIRC, I managed to show, that
for a sufficiently large "elliptic" orbit (with high damping),
(d/dt)|u|^2<=0 regardless of the current damping. Since we are already
considering the "worst possible" input signal, the system state can't
cross this boundary "orbit" to the outside.
For the discrete-time case the situation is more complicated, because we
can't use the continuity of the state vector function. IIRC, I also
didn't manage to build the "worst-case" signal, but there was the same
problem of the state vector becoming larger in the absence of the input
signal. That's why I was somewhat surprised that you simply managed to
restrict the eigenvalues of the system matrix in some coordinates.
Particularly suspicious is that your coordinate transformation matrix is
"built for the smallest damping", while the more problematic case seems
to occur "at the larger damping". But, as I said, I didn't finish that
research and I could have been wrong. So just take my input FWIW.
Regards,
Vadim
-
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 11-Nov-13 01:09, robert bristow-johnson wrote: On 11/8/13 6:47 PM, Andrew Simper wrote: It depends if you value numerical performance, cutoff accuracy, dc performance etc etc, DF1 scores badly on all these fronts, nope. and this is even in the case where you keep your cutoff and q unchanged. Hi Robert, from your reply I understood that you're referring to the parameter quantization, while I think Andy was referring to the state quantization. Furthermore, also parameter quantization seems much less of an issue with the 0df approach, since cos(...) doesn't occur there (although I don't have a rigorous proof). Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 08-Nov-13 12:13, Urs Heckmann wrote: No offense meant, I wasn't aware that your book was considered a standard dsp lecture. If you know of any university that uses it in their curriculum, please let me know and I'll recommend that university. Damn, you got me there ;-) -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 08-Nov-13 10:34, STEFFAN DIEDRICHSEN wrote: If you look at Figure 3.18 of said book, there’s a delay in the feedback path. But it’s done in an elegant way, so no insult here. ;-) Damn, I probably should remove the said Figure (and Figs. 3.19-3.20 for that matter) in the next revision. Thanks for the proofreading! ;-) ;-) ;-) Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 08-Nov-13 03:13, Ross Bencina wrote: Now, I do have one thing I would like to see: and that is a mathematical proof that point (4) above is actually true for this topology. Ever since I read the Laroche BIBO paper it scared the crap out of me to be modulating any IIR filter at audio rate without a trusted analysis. Hi Ross, I once tried to do the analysis you mentioned. IIRC, I managed to successfully show the time-varying BIBO stability of analog 1-pole (this is very simple) and 2-pole (somewhat more tricky) analog SVFs under the condition that the real parts of all poles are "uniformly negative" (that is bound by some negative constant from above). IIRC, it is also quite straightforward to show the time-varying stability of a 2nd-order real Jordan cell (which probably has the best time-varying stability anyway), but this one is not so convenient as the LP/BP/HP multimode SVF. I have no idea if there are papers addressing this. For the discrete-time versions it seemed way more complicated. I couldn't prove it or build a disproving example for the TPT BLT version of the same 2-pole SVF (and I don't remember whether I managed to build a proof for the 1-pole). Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal integrated optimised SVF v2
On 08-Nov-13 10:00, Urs Heckmann wrote: I have however not followed this list in a while, so my apologies if "0df" has been discussed in a wider scope than Andy's papers before - I have yet to see a standard dsp book that covers it. However, products on the market seem sparse thus I think it may not have...? Hi Urs! I don't believe this. So, you think that "The art of VA filter design" book doesn't cover it? Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Fwd: 24dB/oct splitter
(the quotation is from Andy's mail) On 2/8/13 2:15 AM, Ross Bencina wrote: i've analyzed Hal's SVF to death, and i was exposted to Andy's design some time ago, but at first glance, it looks like the "Trapazoidal SVF" looks like it doubles the order of the filter. it it was a second-order analog, it becomes a 4th-order digital. but his final equations do not show that. do those "trapazoidal" integrators, become a single-delay element block (if one were to simplify)? even though they ostensibly have two delays? You can use canonical (DF2/TDF2) trapezoidal integration, in which case the order of the filter doesn't formally grow. This is quite intuitively representable in the TPT papers and the book I mentioned earlier. If you use DF1 integrators, the order formally grows by a factor of 2, but I believe half of the poles will be cancelled by the zeroes. BTW, IIRC, as for the optimization from 4 z^-1 to 3 z^-1 in Andy's SVF, I believe this optimization implicitly assumed the time-invariance of the filter. So, while keeping the transfer function intact, this optimization changes the time-varying behavior of the filter (not sure, how much and whether it's for the worse or for the better). Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] IIR Coefficient Switching Issues
Oh, completely forgot. Here's a step-by-step description of the TPT method: http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign_1.0.3.pdf (A4 format) http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign_1.0.3_A5.pdf (A5 format) On 04-Nov-13 11:07, Vadim Zavalishin wrote: Hi Chris Direct forms are not good for coefficient modulation, plus IIRC they tend to have precision issues at low cutoffs. I guess, the TPT (ZDF) approach can solve your problem completely: http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/KeepTopology.pdf (For the 2nd order filters use the modes of the SVF from the same paper) If you can read Reaktor Core, then here's some additional info: http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/KeepTopologyRC.pdf Regards, Vadim -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] IIR Coefficient Switching Issues
Hi Chris Direct forms are not good for coefficient modulation, plus IIRC they tend to have precision issues at low cutoffs. I guess, the TPT (ZDF) approach can solve your problem completely: http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/KeepTopology.pdf (For the 2nd order filters use the modes of the SVF from the same paper) If you can read Reaktor Core, then here's some additional info: http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/KeepTopologyRC.pdf Regards, Vadim On 03-Nov-13 04:27, Chris Townsend wrote: I'm working on an algorithm with some user controlled "presets" that adjust various IIR filters under the hood. This generally works fine, but I get pops and glitches when switching between certain settings. The filters that are causing trouble are typically second order hipass filters with a sub 100Hz cutoff, but with some settings the filters reconfigure to peaking, shelf and first order hipass types. Generally the problem is most noticeable when changing between types. This appears to be a simple matter of the internal states of the filter being un-normalized and so large gain chances of the state variables can occur when coefficients are adjusted. I read through some old Music-DSP posts on this topic, but I didn't find a clear solution that fit my needs. I'm using 1 pole coefficient smoothing, which helps reduce the glitches but definitely doesn't get rid of them. Currently I'm using DF2 transpose filter topology. I also tried lattice and a couple others topologies, but overall that didn't improve things and in some cases was worse. If I only needed a second order hipass then I would think a Chamberlin State Variable Filter would be my best bet, since I found it to be very adept at handling coefficient changes. But I'm not sure it will work for me, since it's not a fully generally filter topology. I've looked at using the Kingsbury topology which is very similar in form to Chamberlin, but has poles that are generalized. Apparently Kingsbury's filter is all-pole (no zeros), so would need to tack on some zeros to make it fully general, but then I'm not sure it would maintain the nice properties of the Chamberlin filter. I've also looked at using a ladder filter, which seems like it would totally solve my problem, since all of the internal states are normalized. The only downside is that it's about double the computational cost of most other filter topologies, but that's not a huge deal in this case. There's also the possibility of renormalizing the filter states every time the coefficients are updated, but that seems complicated and costly in terms of CPU, since the smoothing updates the coefficients at a fairly high rate. I'm also seeing some coefficient quantization issues at high sample rates, when using DF2T, because I'm dealing with low cutoff frequencies and using single precision floats. It looks like Chamberlin, Kingsbury or Ladder would also perform much better in that respect. Any ideas? Recommendations? Thanks, Chris -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Reaktor Application Architect Native Instruments GmbH +49-30-611035-0 www.native-instruments.com -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
[music-dsp] ANN: Book: The Art of VA Filter Design
Hi all This is kind of a cross-announcement from KVRAudio, but since there are probably a number of different people on this list, I thought I'd announce it here as well. Get it here: http://ay-kedi.narod2.ru/VAFilterDesign.pdf http://images-l3.native-instruments.com/fileadmin/ni_media/downloads/pdf/VAFilterDesign.pdf http://www.discodsp.net/VAFilterDesign.pdf (thanks to "george" for mirroring) There is a discussion thread at http://www.kvraudio.com/forum/viewtopic.php?t=350246 Regards, Vadim -- Vadim Zavalishin Software Integration Architect | R&D Tel +49-30-611035-0 Fax +49-30-611035-2600 NATIVE INSTRUMENTS GmbH Schlesische Str. 29-30 10997 Berlin, Germany http://www.native-instruments.com Registergericht: Amtsgericht Charlottenburg Registernummer: HRB 72458 UST.-ID.-Nr. DE 20 374 7747 Geschaeftsfuehrung: Daniel Haver (CEO), Mate Galic -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Noise performance of f32 iir filters
I'm still waiting to hear the delicious details of Peter's Bacon Lettuce and Tomato Transform As mentioned by the previous answers: BLT = bilinear transform (I think this abbreviation is rather common in DSP) TPT = topology-preserving transform http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/KeepTopology.pdf (there was a discussion on this list how exactly to name this thing, but it seems TPT gets slowly accepted as a term, at least I've already seen it mentioned on the KVR). Regards, Vadim - Original Message - From: "Thomas Young" To: "A discussion list for music-related DSP" Sent: Monday, October 03, 2011 18:48 Subject: Re: [music-dsp] Noise performance of f32 iir filters I'm still waiting to hear the delicious details of Peter's Bacon Lettuce and Tomato Transform -Original Message- From: music-dsp-boun...@music.columbia.edu [mailto:music-dsp-boun...@music.columbia.edu] On Behalf Of Dave Hoskins Sent: 03 October 2011 17:46 To: A discussion list for music-related DSP Subject: Re: [music-dsp] Noise performance of f32 iir filters Nigel Redmon wrote: > (not to mention ATM--geez how many meanings can that one attain?). thefreedictionary.com lists 106 meanings... http://acronyms.thefreedictionary.com/ATM At The Moment, According To Me, the Advanced Testing Method for Automated Theorem Provers is to read the Acceptance Test Manual from the Association of Teachers of Mathematics at the Annual Technical Meeting where they all Ate Too Much! I'll get my coat... : ) D. -- Vadim Zavalishin Senior Software Developer | R&D Tel +49-30-611035-0 Fax +49-30-611035-2600 NATIVE INSTRUMENTS GmbH Schlesische Str. 29-30 10997 Berlin, Germany http://www.native-instruments.com Registergericht: Amtsgericht Charlottenburg Registernummer: HRB 72458 UST.-ID.-Nr. DE 20 374 7747 Geschaeftsfuehrung: Daniel Haver (CEO), Mate Galic -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Noise performance of f32 iir filters
Just for the reference, I tried to measure the precision of the TPT version of the SVF using DF2 BLT integrators, as described in http://www.native-instruments.com/fileadmin/ni_media/downloads/pdf/KeepTopology.pdf If I didn't make any mistakes in the measurements, the 32-bit float precision is better than -100dB for cutoffs below 20kHz at 44.1kHz SR. The error seems to be larger at large cutoffs. As already mentioned, the trapezoidal integration is pretty much equivalent to TPT with DF1 integrators. There was an observation made by Dominique Wurtz on KVRAudio DSP forum, that DF1 and DF2 integrators should behave fully identically (mathematically, ignoring the precision issues) even in the time-varying TPT case. Which pretty much eliminates (mathematically) the need for DF1 integrators in TPT (except in special cases). Regards, Vadim - Original Message - From: "Andrew Simper" To: "A discussion list for music-related DSP" Sent: Tuesday, September 27, 2011 16:19 Subject: Re: [music-dsp] Noise performance of f32 iir filters Hi Earl, Since the analog SVF is one of the lowest noise topologies in analog filters I suspect that a fixed point implementation will do well, but I have not tested it yet. Andy -- cytomic - sound music software On 27 September 2011 21:35, Earl Vickers wrote: Hi Andrew, This looks most impressive. I look forward to seeing your article. Any thoughts on how suitable this topology would be for fixed-point implementation? Earl Andrew Simper wrote: I finally got around to following up on my hunch that a slightly modified version of the trapezoidal integrated svf (ie a modified version of the one I previously posted) should have excellent numerical properties. My initial tests confirm this in spectacular fashion. I used all sorts of tests, but the one to show up most problems was a bell filter with q=2, gain=12 dB, and look at the cutoffs 20, 200, 2k, 20k. I compare the modified state variable filter, normalised ladder, normalised direct wave form, direct form 1, and direct form 2 transposed. The only filter to match the low quantization error of the modified svf is the normalized ladder filter, but none of the filters can match the coefficient rounding error, as is shown in the time domain error of the 20 Hz example: http://www.cytomic.com/files/dsp/SVF-vs-DF1.pdf The modified SVF works fine down to very low frequencies with all single precision computation, which makes it ideal for use even at 192 kHz sample rates. I'll get around to writing it up some time, but I've got a few plugins and other work to get on with for the moment. -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Senior Software Developer | R&D Tel +49-30-611035-0 Fax +49-30-611035-2600 NATIVE INSTRUMENTS GmbH Schlesische Str. 29-30 10997 Berlin, Germany http://www.native-instruments.com Registergericht: Amtsgericht Charlottenburg Registernummer: HRB 72458 UST.-ID.-Nr. DE 20 374 7747 Geschaeftsfuehrung: Daniel Haver (CEO), Mate Galic -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Noise performance of f32 iir filters
Hi Andrew I finally got around to following up on my hunch that a slightly modified version of the trapezoidal integrated svf (ie a modified version of the one I previously posted) should have excellent numerical properties. Care to reveal what is the "modification"? Did you measure the precision of the "unmodified" version? Regards, Vadim - Original Message - From: "Andrew Simper" To: "A discussion list for music-related DSP" Sent: Tuesday, September 27, 2011 10:09 Subject: [music-dsp] Noise performance of f32 iir filters I finally got around to following up on my hunch that a slightly modified version of the trapezoidal integrated svf (ie a modified version of the one I previously posted) should have excellent numerical properties. My initial tests confirm this in spectacular fashion. I used all sorts of tests, but the one to show up most problems was a bell filter with q=2, gain=12 dB, and look at the cutoffs 20, 200, 2k, 20k. I compare the modified state variable filter, normalised ladder, normalised direct wave form, direct form 1, and direct form 2 transposed. The only filter to match the low quantization error of the modified svf is the normalized ladder filter, but none of the filters can match the coefficient rounding error, as is shown in the time domain error of the 20 Hz example: http://www.cytomic.com/files/dsp/SVF-vs-DF1.pdf The modified SVF works fine down to very low frequencies with all single precision computation, which makes it ideal for use even at 192 kHz sample rates. I'll get around to writing it up some time, but I've got a few plugins and other work to get on with for the moment. -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp -- Vadim Zavalishin Senior Software Developer | R&D Tel +49-30-611035-0 Fax +49-30-611035-2600 NATIVE INSTRUMENTS GmbH Schlesische Str. 29-30 10997 Berlin, Germany http://www.native-instruments.com Registergericht: Amtsgericht Charlottenburg Registernummer: HRB 72458 UST.-ID.-Nr. DE 20 374 7747 Geschaeftsfuehrung: Daniel Haver (CEO), Mate Galic -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal andotherintegrationmethodsappliedtomusical resonant filters
With regard to stability under time varying modulation, Jean Laroche has published some criteria: Very interesting! As to analysing the effect of parameter modulation on the output I guess this is a job for state-space models? Yes, I guess this is easiest to analyse in the state-space form. Regards, Vadim -- Vadim Zavalishin Senior Software Developer | R&D Tel +49-30-611035-0 Fax +49-30-611035-2600 NATIVE INSTRUMENTS GmbH Schlesische Str. 28 10997 Berlin, Germany http://www.native-instruments.com Registergericht: Amtsgericht Charlottenburg Registernummer: HRB 72458 UST.-ID.-Nr. DE 20 374 7747 Geschaeftsfuehrung: Daniel Haver (CEO), Mate Galic -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal and other integrationmethodsappliedtomusical resonant filters
sound to an extent. When comparing the models, one also shouldn't forget the time-variant (modulated parameters) behavior of the structures (which I guess is the primary reason to use SVF instead of DF), but this is much more difficult to theoretically analyse. With regards time varying aspects it is easy to solve for them as well. What I meant is not the time-varying implementation, which of course is not difficult in the cases you describe. I was referring to the question of analysing how close is the digital model to the analog one in the time-varying case. For the time-invariant case we have the transfer function as our analysis tool, giving us full information about both versions of the system (so that we can e.g. say that bilinear-transformed implementations have amplitude/phase responses pretty close to their continuous time prototypes). However, the same thing doesn't work in the time-variant case. Thus, we typically just perform experimental analysis of the time-variant behavior (which, for music DSP purposes, includes the stability and the effect of parameter modulation on the output). Regards, Vadim -- Vadim Zavalishin Senior Software Developer | R&D Tel +49-30-611035-0 Fax +49-30-611035-2600 NATIVE INSTRUMENTS GmbH Schlesische Str. 28 10997 Berlin, Germany http://www.native-instruments.com Registergericht: Amtsgericht Charlottenburg Registernummer: HRB 72458 UST.-ID.-Nr. DE 20 374 7747 Geschaeftsfuehrung: Daniel Haver (CEO), Mate Galic -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal and other integrationmethodsappliedtomusical resonant filters
Just one other issue I wanted to mention in respect to using trapezoidal integration / bilinear TPT vs. trying to "manually" fix "simpler" Euler-like models. Besides giving a nice frequency response of a digital model, the BLT also results in an "equally nice" phase response, which also affects the sound to an extent. When comparing the models, one also shouldn't forget the time-variant (modulated parameters) behavior of the structures (which I guess is the primary reason to use SVF instead of DF), but this is much more difficult to theoretically analyse. Regards, Vadim -- Vadim Zavalishin Senior Software Developer | R&D Tel +49-30-611035-0 Fax +49-30-611035-2600 NATIVE INSTRUMENTS GmbH Schlesische Str. 28 10997 Berlin, Germany http://www.native-instruments.com Registergericht: Amtsgericht Charlottenburg Registernummer: HRB 72458 UST.-ID.-Nr. DE 20 374 7747 Geschaeftsfuehrung: Daniel Haver (CEO), Mate Galic -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
Re: [music-dsp] Trapezoidal and other integration methodsappliedtomusical resonant filters
okay, so that's an analog resonant LPF filter. there is a method, called "impulse invariant" (an alternative to BLT) to transform this analog filter to a digital filter. as it's name suggests, we have a digital impulse response that looks the same (again, leaving out the unit step gating function): Just for the record. The digital impulse response indeed looks exactly the same, but (!) it is not bandlimited, which results in distorted frequency response of the resulting filter. Bandlimiting the response is not a solution either, because the resulting response then is not a response of a system consisting of a finite number of unit delays. Vadim, is this the article you meant? Fontana, "Preserving the structure of the Moog VCF in the digital domain" Proc. Int. Computer Music Conf., Copenhagen, Denmark, 27-31 Aug. 2007 http://quod.lib.umich.edu/cgi/p/pod/dod-idx?c=icmc;idno=bbp2372.2007.062 Yes, thanks Martin. BTW, I'f I'm correct, this paper (I only briefly looked through it) doesn't address fixing the problem in the 1-pole components. It's correct that the bigger problem is in the outer feedback loop, but performing the same fix in the 1-poles improves the behavior further, IIRC. -- it does beg the question: why didn't we think of this earlier? and why did Chamberlin do it the way he did? A number of people *did* think of this earlier, also in the application to the analog simulation. E.g. the simulanalog.org article I mentioned earlier uses trapezoidal integration, and I would guess that there is even some earlier work. The right question is: why almost nobody cares about this issue? Yet another issue, is the subjectivity of the judgement. Not all DSP engineers, and even not all musicians have the same high requirements to the details of the filter response. Many people would be fully happy with the Chamberlin SVF as it is. Also, BLT filters require division (once the parameters change), which was quite expensive, especially those days, I think. Regards, Vadim -- Vadim Zavalishin Senior Software Developer | R&D Tel +49-30-611035-0 Fax +49-30-611035-2600 NATIVE INSTRUMENTS GmbH Schlesische Str. 28 10997 Berlin, Germany http://www.native-instruments.com Registergericht: Amtsgericht Charlottenburg Registernummer: HRB 72458 UST.-ID.-Nr. DE 20 374 7747 Geschaeftsfuehrung: Daniel Haver (CEO), Mate Galic -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
