Re: [music-dsp] Computational complexity of common DSP algorithms

On Thu, Mar 19, 2020 at 8:11 AM Dario Sanfilippo wrote: > > I believe that the time complexity of FFT is O(nlog(n)); would you perhaps > have a list or reference to a paper that shows the time complexity of > common DSP systems such as a 1-pole filter? > The complexity depends on the topology.

[music-dsp] Sliding Phase Vocoder (was FIR blog post & interactive demo)

On Tue, Mar 10, 2020 at 1:05 PM Richard Dobson wrote: > > Our ICMC paper can be found here, along with a few beguiling sound > examples: > > http://dream.cs.bath.ac.uk/SDFT/ So this is pretty cool stuff. I can't say I've digested the whole idea yet, but I had a couple of obvious questions. In

Re: [music-dsp] FIR blog post & interactive demo

dio if you want to hear whether or not there is quantization noise from > this FFT EQ or not (from changing the coefficients, etc). > > > cheers, > Eric Z > https://www.github.com/kardashevian > > On Fri, Mar 13, 2020 at 6:18 PM Ethan Duni wrote: > >> On Thu, Mar 12, 2020 at

Re: [music-dsp] FIR blog post & interactive demo

On Thu, Mar 12, 2020 at 9:35 PM robert bristow-johnson < r...@audioimagination.com> wrote: > i am not always persuaded that the analysis window is preserved in the > frequency-domain modification operation. It definitely is *not* preserved under modification, generally. The Perfect

Re: [music-dsp] FIR blog post & interactive demo

Hi Robert On Wed, Mar 11, 2020 at 4:19 PM robert bristow-johnson < r...@audioimagination.com> wrote: > > i don't think it's too generic for "STFT processing". step #4 is pretty > generic. > I think the part that chafes my intuition is more that the windows in steps #2 and #6 should "match" in

Re: [music-dsp] FIR blog post & interactive demo

On Tue, Mar 10, 2020 at 8:36 AM Spencer Russell wrote: > > The point I'm making here is that overlap-add fast FIR is a special case > of STFT-domain multiplication and resynthesis. I'm defining the standard > STFT pipeline here as: > > 1. slice your signal into frames > 2. pointwise-multiply an

Re: [music-dsp] FIR blog post & interactive demo

> On Mar 10, 2020, at 3:38 AM, Richard Dobson wrote: > > You can have windows when hop size is 1 sample (as used in the sliding phase > vocoder (SPV) proposed by Andy Moorer exactly 20 years ago, and the focus of > a research project I was part of around 2007). So long as the window is based

Re: [music-dsp] FIR blog post & interactive demo

It is certainly possible to combine STFT with fast convolution in various ways. But doing so imposes significant overhead costs and constrains the overall design in strong ways. For example, this approach: > On Mar 9, 2020, at 7:16 AM, Spencer Russell wrote: > >  > if you have an KxN STFT

Re: [music-dsp] FIR blog post & interactive demo

On Sun, Mar 8, 2020 at 8:02 PM Spencer Russell wrote: > In fact, the the standard STFT analysis/synthesis pipeline is the same > thing as overlap-add "fast convolution" if you: > > 1. Use a rectangular window with a length equal to your hop size > 2. zero-pad each input frame by the length of

Re: [music-dsp] FIR blog post & interactive demo

> > If the system is suitably designed (e.g. correct window and overlap), > you can filter using an FFT and get identical results to a time domain > FIR filter (up-to rounding/precision limits, of course). The > appropriate window and overlap process will cause all circular > convolution

Re: [music-dsp] FIR blog post & interactive demo

or > DCT type IV which is ubiquitous in audio codecs. > >> On Sun, Mar 8, 2020, 7:41 PM Ethan Duni wrote: >> FFT filterbanks are time variant due to framing effects and the circular >> convolution property. They exhibit “perfect reconstruction” if you design >&

Re: [music-dsp] FIR blog post & interactive demo

FFT filterbanks are time variant due to framing effects and the circular convolution property. They exhibit “perfect reconstruction” if you design the windows correctly, but this only applies if the FFT coefficients are not altered between analysis and synthesis. If you alter the FFT

Re: [music-dsp] FIR blog post & interactive demo

It is physically impossible to build a causal, zero-phase system with non-trivial frequency response. Ethan > On Mar 7, 2020, at 7:42 PM, Zhiguang Eric Zhang wrote: > >  > Not to threadjack from Alan Wolfe, but the FFT EQ was responsive written in C > and running on a previous gen MacBook

Re: [music-dsp] high & low pass correlated dither noise question

So as Nigel and Robert have already explained, in general you need to separately handle the spectral shaping and pdf shaping. This dither algorithm works by limiting to the particular case of triangular pdf with a single pole at z=+/-1. For that case, the state of the spectral shaping filter can

Re: [music-dsp] Who uses YIN or pYIN for pitch detection?

Looks like they use the Viterbi algorithm to get the pitch tracks. > On Mar 6, 2019, at 6:59 PM, Jay wrote: > > > Looks like there's a link to a python implementation on this topics page, > might provide some insights: > https://github.com/topics/pitch-tracking > > > > > > > > >> On

Re: [music-dsp] Auto-tune sounds like vocoder

Aren't Auto-Tune and similar built on LPC vocoders? I had the impression that was publicly known (recalling magazine interviews/articles from the late 90s). The secret sauce being all the stuff required for pitch tracking, unvoiced segments, different tunings, vibrato, corner cases, etc. But as

Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for realtime synthesis?

cations? > > The background is still that I want to use a higher resolution for > ananlysis and > a lower resolution for synthesis in a phase vocoder. > > Am 08.11.2018 um 21:45 schrieb Ethan Duni: > > Not sure can get the odd bins *easily*, but it is certainly possible. > Con

Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for realtime synthesis?

t; X1 = x0 + (r - r*i)*x1 - i*x2 + (-r - r*i)*x3 - x4 + (-r + r*i)*x5 + i*x6 > + (r + r*i)*x7 > > where r=sqrt(1/2) > > Is it actually possible? It seems like the phase of the coefficients in > the Y's and Z's advance too quickly to be of any use. > > -Ethan > > > &

Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for realtime synthesis?

You can combine consecutive DFTs. Intuitively, the basis functions are periodic on the transform length. But it won't be as efficient as having done the big FFT (as you say, the decimation in time approach interleaves the inputs, so you gotta pay the piper to unwind that). Note that this is for

Re: [music-dsp] Antialiased OSC

Well you definitely want a monotonic, equal-amplitude crossfade, and probably also time symmetry. So I think raised sinc is right out. In terms of finer design considerations it depends on the time scale. For longer crossfades (>100ms), steady-state considerations apply, and you can design for

Re: [music-dsp] pitch shifting in frequency domain Re: FFT for realtime synthesis?

You should have a search for papers by Jean Laroche and Mark Dolson, such as "About This Phasiness Business" for some good information on phase vocoder processing. They address time scale modification mostly in that specific paper, but many of the insights apply in general, and you will find

Re: [music-dsp] Resampling

Alex, it sounds like you are confusing algorithmic latency with framing latency. At each frame, you take in 10ms (or whatever) of input, and then provide 10ms of output. This (plus processing time to generate the output) is the IO latency of the process. But the algorithm itself can add

Re: [music-dsp] Antialiased OSC

rbj wrote: >i, personally, would rather see a consistent method used throughout the MIDI keyboard range If you squint at it hard enough, you can maybe convince yourself that the naive sawtooth generator is just a memory optimization for low-frequency wavetable entries. I mean, it does a perfect

Re: [music-dsp] Clock drift and compensation

Hi ben You don't need to evaluate the asin() - it's piecewise monotonic and symmetrical, so you can get the same comparison directly in the signal domain. Specifically, notice that x(n) = sin(2*pi*(1/4)*n) = [...0,1,0,-1,...]. So you get the same result just by checking ( abs( x[n] - x[n-1] ) ==

Re: [music-dsp] Sampling theory "best" explanation

com> wrote: > > > Original Message > Subject: Re: [music-dsp] Sampling theory "best" explanation > From: "Ethan Duni" <ethan.d...@gmail.com> > Date: Wed, September 6, 2017 4:49 pm > To

Re: [music-dsp] Sampling theory "best" explanation

rry you misinterpreted it. > > On Sep 7, 2017, at 5:34 AM, Ethan Duni <ethan.d...@gmail.com> wrote: > > Nigel Redmon wrote: > >As an electrical engineer, we find great humor when people say we can't > do impulses. > > I'm the electrical engineer who pointed out t

Re: [music-dsp] Sampling theory "best" explanation

e shortcut is trivial. Like I said, audio > sample rates are slow, not that hard to do a good enough job for > demonstration with "close enough" impulses. > > Don't anyone get mad at me, please. Just sitting on a plane at LAX at 1AM, > waiting to fly 14 hours...on the

Re: [music-dsp] Sampling theory "best" explanation

esenting bandlimited functions is useful. Because if we're thinking >> of things this way, we can simply define an operation in the space of >> discrete signals as being LTI iff the corresponding operation in the space >> of bandlimited functions is LTI. This generalizes the usual d

Re: [music-dsp] Sampling theory "best" explanation

o violate the > definition of LTI they were taught. > > On Sep 1, 2017, at 3:46 PM, Ethan Duni <ethan.d...@gmail.com> wrote: > > Ethan F wrote: > >I see your nitpick and raise you. :o) Surely there are uncountably many > such functions, > >as the power at any ap

Re: [music-dsp] Sampling theory "best" explanation

adio >> applications. > > > I see your nitpick and raise you. :o) Surely there are uncountably many > such functions, as the power at any apparent frequency can be distributed > arbitrarily among the bands. > > -Ethan F > > > On Fri, Sep 1, 2017 at 5:30 PM, Ethan

Re: [music-dsp] Sampling theory "best" explanation

>I'm one of those people who prefer to think of a discrete-time signal as >representing the unique bandlimited function interpolating its samples. This needs an additional qualifier, something about the bandlimited function with the lowest possible bandwidth, or containing DC, or "baseband," or

Re: [music-dsp] advice regarding USB oscilloscope

These PicoScopes look pretty cool :] As it happens I am just now trying to free up some garage space to get an electronics bench together. But it's coming up on 20 years since I last soldered and it's a whole different world with scopes now. So thanks for this thread! Also if anybody knows good

Re: [music-dsp] ± 45° Hilbert transformer using pair of IIR APFs

> how do you quadrature modulate without Hilbert filters? > Perhaps I'm using the wrong term - the operation in question is just the multiplication of a signal by e^jwn. Or, equivalently, multiplying the real part by cos(wn) and the imaginary part by sin(wn) - a pair of "quadrature oscillators."

Re: [music-dsp] ± 45° Hilbert transformer using pair of IIR APFs

On Tue, Feb 7, 2017 at 6:49 AM, Ethan Fenn wrote: > So I guess the general idea with these frequency shifters is something > like: > > pre-filter -> generate Hilbert pair -> multiply by e^iwt -> take the real > part > > Am I getting that right? > Exactly, this is a

Re: [music-dsp] Can anyone figure out this simple, but apparently wrong, mixing technique?

Ha this article made me chuckle. All the considerations about odd 8 bit audio formats! This method has his desired property that if all but one input is silent, you get the non-silent one at output without attenuation or other degradation. But the inclusion of the cross term makes it quite

Re: [music-dsp] Allpass filter

sponse and truncate/window it to the desired length. FFT domain is generally not a good place to design filters - you're only controlling what happens at the bin centers, and all kinds of wild things can happen in between them. And it's difficult to account for the circular/finite length effects.

Re: [music-dsp] efficient running max algorithm

Right aren't monotonic signals the worst case here? Or maybe not, since they're worst for one wedge, but best for the other? Ethan D On Fri, Sep 2, 2016 at 10:12 AM, Evan Balster wrote: > Just a few clarifications: > > - Local maxima and first difference don't really matter.

Re: [music-dsp] idealized flat impact like sound

So like a cascade of allpass filters then? Ethan D On Fri, Jul 29, 2016 at 11:10 AM, gm wrote: > > I think what I am looking for would be the perfect reverb. > > So that's the question reformulated: how could you construct a perfectly > flat short reverb? > > It's the

Re: [music-dsp] Anyone using unums?

>okay, this PDF was more useful than the other. once i got down to slide #31, > i could see the essential definition of what a "unum" is. >big deeel. >first of all, if the word size is fixed and known (and how would you know how far >to go to get to the extra meta-data: inexact bit, num

Re: [music-dsp] High quality really broad bandwidth pinknoise (ideally more than 32 octaves)

Any noise other than white noise is correlated, by definition. That's what "white noise" means - uncorrelated. Correlation in the time domain is equivalent to non-constant shape in the frequency domain. Ethan On Thu, Apr 14, 2016 at 12:24 PM, Seth Nickell wrote: > Maybe

Re: [music-dsp] confirm a2ab2276c83b0f9c59752d823250447ab4b666

Supposing this is some griefer it seems reasonable to ignore them - but is there a possibility that this is a symptom of some kind of server attack or attempt to profile/track list members? I've never received any unsub notices myself but it is a little disconcerting that somebody persists at

Re: [music-dsp] Changing Biquad filter coefficients on-the-fly, how to handle filter state?

Yeah zeroing out the state is going to lead to a transient, since the filter has to ring up. If you want to go that route, one possibility is to use two filters in parallel: one that keeps the old state/coeffs but gets zero input, and another that has zero state and gets the new input/coeffs. You

Re: [music-dsp] Cheap spectral centroid recipe

Theo wrote: >I get there are certain statistical ideas involved. I wonder >however where those ideas in practice lead to, because >of a number of assumptions, like the "statistical variance" >of a signal. I get that a self correlation of a signal in some >normal definition gives an idea of the

Re: [music-dsp] Cheap spectral centroid recipe

>Lastly, it's important to note that differentiation and semi-differentiation >filters are always approximate for sampled signals, and will tend to >exhibit poor behavior for very high frequencies and (for semi-differentiation) >very low ones. I'm not sure there's necessarily a problem at low

Re: [music-dsp] Time-domain noisiness estimator

Not a purely time-domain approach, but you can consider comparing sparsity in the time and Fourier domains. The idea is that periodic/tonal type signals may be non-sparse in the time domain, but look sparse in the frequency domain (because all of the energy is on/around harmonics). Similarly,

Re: [music-dsp] Cheap spectral centroid recipe

ny brightness metric can be clearly understood, I'll stick > to formulas whose mathematical properties are transparent -- these lend > themselves infinitely better to being small pieces of larger systems. > > – Evan Balster > creator of imitone <http://imitone.com> > &g

Re: [music-dsp] Cheap spectral centroid recipe

s with the differential brightness estimator. > > – Evan Balster > creator of imitone <http://imitone.com> > > On Thu, Feb 18, 2016 at 1:00 AM, Ethan Duni <ethan.d...@gmail.com> wrote: > >> >normalized to fundamental frequency or not >> >normalized (so t

Re: [music-dsp] Cheap spectral centroid recipe

om> wrote: > > > Original Message > Subject: Re: [music-dsp] Cheap spectral centroid recipe > From: "Ethan Duni" <ethan.d...@gmail.com> > Date: Wed, February 17, 2016 11:21 pm > To: "A discussion list f

Re: [music-dsp] Cheap spectral centroid recipe

>It's essentially computing a frequency median, >rather than a frequency mean as is the case >with the derivative-power technique described > in my original approach. So I'm wondering, is there any consensus on what is the best measure of central tendency for a music signal spectrum? There's the

Re: [music-dsp] Anyone using Chebyshev polynomials to approximate trigonometric functions in FPGA DSP

>given the same order N for the polynomials, whether your basis set are > the Tchebyshevs, T_n(x), or the basis is just set of x^n, if you come up >with a min/max optimal fit to your data, how can the two polynomials be >different? Right, if you do that you'll end up with equivalent answers (to

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

>> [..] the autocorrelation is >> >> = (1/3)*(1-P)^|k| >> >> (I checked that with a little MC code before posting.) So the power >> spectrum is (1/3)/(1 + (1-P)z^-1) The FT of (1/3)*(1-P)^|k| is (1/3)*(1-Q^2)/(1-2Qcos(w) + Q^2), where Q = (1-P). Looks like you were thinking of the

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

- > Subject: Re: [music-dsp] how to derive spectrum of random sample-and-hold > noise? > From: "Ethan Duni" <ethan.d...@gmail.com> > Date: Wed, November 11, 2015 7:36 pm > To: "robert bristow-jo

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

-- > Subject: Re: [music-dsp] how to derive spectrum of random sample-and-hold > noise? > From: "Ethan Duni" <ethan.d...@gmail.com> > Date: Wed, November 11, 2015 5:57 pm > To: "robert bristow-johnson" <r...@audioimaginatio

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

On Tue, Nov 10, 2015 at 6:33 PM, robert bristow-johnson < r...@audioimagination.com> wrote: > > > Original Message > Subject: Re: [music-dsp] how to derive spectrum of random sample-and-hold > noise? > From: &

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

>(Semi-)stationarity, I'd say. Ergodicity is a weaker condition, true, >but it doesn't then really capture how your usual L^2 correlative >measures truly work. I think we need both conditions, no? >Something like that, yes, except that you have to factor in aliasing. What aliasing? Isn't this

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

's the basic idea. https://en.wikipedia.org/wiki/Spectral_density_estimation E On Thu, Nov 5, 2015 at 2:00 AM, Ross Bencina <rossb-li...@audiomulch.com> wrote: > Thanks Ethan(s), > > I was able to follow your derivation. A few questions: > > On 4/11/2015 7:07 PM, E

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

about power per linear or angular frequency. And >>> there could be others I'm not thinking of maybe someone else can >>> shed more light here. >>> >> >> I multiplied the psd by 1/3 and as you can see from the graph it looks as >> thoug

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

P^2) Unless I've screwed up somewhere? E On Tue, Nov 3, 2015 at 8:51 PM, Ross Bencina <rossb-li...@audiomulch.com> wrote: > On 4/11/2015 5:26 AM, Ethan Duni wrote: > >> Do you mean the literal Fourier spectrum of some realization of this >> process, or the power spec

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

Yep that's the same approach I just posted :] E On Tue, Nov 3, 2015 at 11:48 PM, Ethan Fenn wrote: > How about this: > > For a lag of t, the probability that no new samples have been accepted is > (1-P)^|t|. > > So the autocorrelation should be: > > AF(t) =

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

Wait, just realized I wrote that last part backwards. It should be: So in broad strokes, what you should see is a lowpass spectrum parameterized by P - for P very small, you approach a DC spectrum, and for P close to 1 you approach a spectrum that's flat. On Tue, Nov 3, 2015 at 10:26 AM, Ethan

Re: [music-dsp] how to derive spectrum of random sample-and-hold noise?

Do you mean the literal Fourier spectrum of some realization of this process, or the power spectral density? I don't think you're going to get a closed-form expression for the former (it has a random component). For the latter what you need to do is work out an expression for the autocorrelation

Re: [music-dsp] Fourier and its negative exponent

>the reason why it's merely convention is that if the minus sign was swapped >between the forward and inverse Fourier transform in all of the literature and >practice, all of the theorems would work the same as they do now. Note that in some other areas they do actually use other conventions.

Re: [music-dsp] Compensate for interpolation high frequency signal loss

think we're on the same page. ain't we? Yeah, I was unclear on which scenario(s) the aliasing analysis was supposed to apply to. E On Wed, Aug 26, 2015 at 12:53 PM, robert bristow-johnson r...@audioimagination.com wrote: On 8/25/15 7:08 PM, Ethan Duni wrote: if you can, with optimal

Re: [music-dsp] Compensate for interpolation high frequency signal loss

, not a discrete time signal of whatever sampling rate. E On Fri, Aug 21, 2015 at 2:09 AM, Peter S peter.schoffhau...@gmail.com wrote: On 21/08/2015, Ethan Duni ethan.d...@gmail.com wrote: In this graph, the signal frequency seems to be 250 Hz, so this graph shows the equivalent of about 22000/250 = 88x

Re: [music-dsp] Compensate for interpolation high frequency signal loss

, 2015 at 1:24 PM, Peter S peter.schoffhau...@gmail.com wrote: On 21/08/2015, Ethan Duni ethan.d...@gmail.com wrote: It shows *exactly* the aliasing It shows the aliasing left by linear interpolation into the continuous time domain. It doesn't show the additional aliasing produced

Re: [music-dsp] Compensate for interpolation high frequency signal loss

...@gmail.com wrote: On 21/08/2015, Ethan Duni ethan.d...@gmail.com wrote: Creating a 22000 Hz signal from a 250 Hz signal by interpolation, is *exactly* upsampling That is not what is shown in that graph. The graph simply shows the continuous-time frequency response of the interpolation

Re: [music-dsp] Compensate for interpolation high frequency signal loss

The details of how the graphs were generated don't really matter. The point is that the only effect shown is the spectrum of the continuous-time polynomial interpolator. The additional spectral effects of delaying and resampling that continuous-time signal (to get fractional delay, for example)

Re: [music-dsp] Compensate for interpolation high frequency signal loss

to what I'm saying in the first place. It is indeed a waste of your time to invent equivalent ways to generate graphs, since that is not the point. E On Fri, Aug 21, 2015 at 2:56 PM, Peter S peter.schoffhau...@gmail.com wrote: On 21/08/2015, Ethan Duni ethan.d...@gmail.com wrote: The details

Re: [music-dsp] Compensate for interpolation high frequency signal loss

1) Olli Niemiatalo's graph *is* equivalent of the spectrum of upsampled white noise. We've been over this repeatedly, including in the very post you are responding to. The fact that there are many ways to produce a graph of the interpolation spectrum is not in dispute, nor is it germaine to my

Re: [music-dsp] Compensate for interpolation high frequency signal loss

of the noisiness no matter how much data you throw at it). E On Fri, Aug 21, 2015 at 5:47 PM, Peter S peter.schoffhau...@gmail.com wrote: On 22/08/2015, Ethan Duni ethan.d...@gmail.com wrote: We've been over this repeatedly, including in the very post you are responding to. The fact

Re: [music-dsp] Compensate for interpolation high frequency signal loss

In this graph, the signal frequency seems to be 250 Hz, so this graph shows the equivalent of about 22000/250 = 88x oversampling. That graph just shows the frequency responses of various interpolation polynomials. It's not related to oversampling. E On Thu, Aug 20, 2015 at 5:40 PM, Peter S

Re: [music-dsp] Compensate for interpolation high frequency signal loss

If all you're trying to do is mitigate the rolloff of linear interp That's one concern, and by itself it implies that you need to oversample by at least some margin to avoid having a zero at the top of your audio band (along with a transition band below that). But the larger concern is the

Re: [music-dsp] Compensate for interpolation high frequency signal loss

a first-order interpolator. quite familiar with it. Yeah that was more for the list in general, to keep this discussion (semi-)grounded. E On Wed, Aug 19, 2015 at 9:15 AM, robert bristow-johnson r...@audioimagination.com wrote: On 8/18/15 11:46 PM, Ethan Duni wrote: for linear

Re: [music-dsp] Compensate for interpolation high frequency signal loss

and it doesn't require a table of coefficients, like doing higher-order Lagrange or Hermite would. Well, you can compute those at runtime if you want - and you don't need a terribly high order Lagrange interpolator if you're already oversampled, so it's not necessarily a problematic overhead.

Re: [music-dsp] Compensate for interpolation high frequency signal loss

. E On Wed, Aug 19, 2015 at 3:55 PM, Peter S peter.schoffhau...@gmail.com wrote: On 20/08/2015, Ethan Duni ethan.d...@gmail.com wrote: I don't dispute that linear fractional interpolation is the right choice if you're going to oversample by a large ratio. The question is what

Re: [music-dsp] Compensate for interpolation high frequency signal loss

rbj and it doesn't require a table of coefficients, like doing higher-order Lagrange or Hermite would. Robert I think this is where you lost me. Wasn't the premise that memory was cheap, so we can store a big prototype FIR for high quality 512x oversampling? So why are we then worried about the

Re: [music-dsp] Compensate for interpolation high frequency signal loss

Assume you have a Nyquist frequency square wave: 1, -1, 1, -1, 1, -1, 1, -1... The sampling theorem requires that all frequencies be *below* the Nyquist frequency. Sampling signals at exactly the Nyquist frequency is an edge case that sort-of works in some limited special cases, but there is no

Re: [music-dsp] Compensate for interpolation high frequency signal loss

a nyquist frequency sinusoid when you run it through a DAC. E On Tue, Aug 18, 2015 at 1:28 PM, Peter S peter.schoffhau...@gmail.com wrote: On 18/08/2015, Ethan Duni ethan.d...@gmail.com wrote: Assume you have a Nyquist frequency square wave: 1, -1, 1, -1, 1, -1, 1, -1... The sampling

Re: [music-dsp] Compensate for interpolation high frequency signal loss

no bearing on the frequency response of fractional interpolators. I'd suggest dropping this whole derail, if you are no longer hung up on this point. E On Tue, Aug 18, 2015 at 2:08 PM, Peter S peter.schoffhau...@gmail.com wrote: On 18/08/2015, Ethan Duni ethan.d...@gmail.com wrote: That class

Re: [music-dsp] Compensate for interpolation high frequency signal loss

, the aliasing issue works like this: I add two numbers together, and find that the answer is X. I tell you X, and then ask you to determine what the two numbers were. Can you do it? E On Tue, Aug 18, 2015 at 2:13 PM, Peter S peter.schoffhau...@gmail.com wrote: On 18/08/2015, Ethan Duni ethan.d

Re: [music-dsp] Compensate for interpolation high frequency signal loss

be used there. But the example of the weird things that can happen when you try to sample a sine wave right at the nyquist rate and then process it is orthogonal to that point. E On Tue, Aug 18, 2015 at 1:16 PM, robert bristow-johnson r...@audioimagination.com wrote: On 8/18/15 3:44 PM, Ethan Duni

Re: [music-dsp] Compensate for interpolation high frequency signal loss

In order to reconstruct that sinusoid, you'll need a filter with an infinitely steep transition band. No, even an ideal reconstruction filter won't do it. You've got your +Nyquist component sitting right on top of your -Nyquist component. Hence the aliasing. The information has been lost in the

Re: [music-dsp] Compensate for interpolation high frequency signal loss

for linear interpolation, if you are a delayed by 3.5 samples and you keep that delay constant, the transfer function is H(z) = (1/2)*(1 + z^-1)*z^-3 that filter goes to -inf dB as omega gets closer to pi. Note that this holds for symmetric fractional delay filter of any odd order (i.e.,

Re: [music-dsp] Compensate for interpolation high frequency signal loss

Yeah I am also curious. It's not obvious to me where it would make sense to spend resources compensating for interpolation rather than just juicing up the interpolation scheme in the first place. E On Mon, Aug 17, 2015 at 11:39 AM, Nigel Redmon earle...@earlevel.com wrote: Since compensation

[music-dsp] This seems relevant to the list of late

https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect E ___ music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp

Re: [music-dsp] about entropy encoding

to address the source of your hostility, and also that you gain more insight into Information Theory. My apologies to the list for encouraging this unfortunate tangent. E On Thu, Jul 16, 2015 at 8:38 PM, Peter S peter.schoffhau...@gmail.com wrote: On 17/07/2015, Ethan Duni ethan.d...@gmail.com

Re: [music-dsp] about entropy encoding

peter.schoffhau...@gmail.com wrote: On 15/07/2015, Ethan Duni ethan.d...@gmail.com wrote: Right, this is an artifact of the approximation you're doing. The model doesn't explicitly understand periodicity, but instead only looks for transitions, so the more transitions per second (higher

Re: [music-dsp] about entropy encoding

This algorithm gives an entropy rate estimate approaching zero for any periodic waveform, irregardless of the shape (assuming the analysis window is large enough). But, it seems that it does *not* approach zero. If you fed an arbitrarily long periodic waveform into this estimator, you won't see

Re: [music-dsp] about entropy encoding

into muddier and muddier waters as it proceeds, and the resulting confusion seems to be provoking some unpleasantly combative behavior from you. E On Thu, Jul 16, 2015 at 12:50 PM, Peter S peter.schoffhau...@gmail.com wrote: On 16/07/2015, Ethan Duni ethan.d...@gmail.com wrote: But, it seems

Re: [music-dsp] about entropy encoding

I wondered a few times what a higher entropy estimate for a higher frequency would mean according to this - I think it means that a higher frequency signal needs a higher bandwidth channel to transmit, as you need a transmission rate of 2*F to transmit a periodic square wave of frequency F. Hence,

Re: [music-dsp] about entropy encoding

Well, I was thinking about this as well. How about a 1bit square wave then? Such a signal is deterministic and so has entropy rate of zero. Your bitflip counter would not be sensitive to duty cycle. The simpler bit counter would be. I don't see why entropy should change with duty cycle since I

Re: [music-dsp] Sampling theorem extension

, and then downsampling? Is there mileage to be had by combining oversampling with BLEP? E On Thu, Jun 25, 2015 at 1:34 AM, Vadim Zavalishin vadim.zavalis...@native-instruments.de wrote: On 24-Jun-15 21:30, Ethan Duni wrote: Could you expand a bit on exactly what it means to apply the BLEP method

Re: [music-dsp] Sampling theorem extension

at 12:49 PM, Sampo Syreeni de...@iki.fi wrote: On 2015-06-12, Ethan Duni wrote: Thanks for expanding on that, this is quite interesting stuff. However, if I'm following this correctly, it seems to me that the problem of multiplication of distributions means that the whole basic set-up

Re: [music-dsp] Sampling theorem extension

to sampling/reconstruction of well-tempered distributions in the first place. No? E On Thu, Jun 11, 2015 at 2:00 AM, Sampo Syreeni de...@iki.fi wrote: On 2015-06-09, Ethan Duni wrote: The Fourier transform does not exist for functions that blow up to +- infinity like that. To do frequency domain

Re: [music-dsp] Sampling theorem extension

vadim.zavalis...@native-instruments.de wrote: 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

Re: [music-dsp] Sampling theorem extension

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

Re: [music-dsp] Did anybody here think about signal integrity

Now the assignment is as follows: can we, given the output signal coming from our filter which was fed the input signal, and the filter coefficients, compute the input signal ? Invertible digital filters are invertible, up to numerical precision. Are you wanting to talk about finite word length

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

Re: [music-dsp] [ot] what is GL_TEXTURE_2D_MULTISAMPLE??

Wow, good answer! E On Sat, Jun 6, 2015 at 4:34 PM, Sampo Syreeni de...@iki.fi wrote: On 2015-06-06, Alan Wolfe wrote: I am so sorry... meant to send this to myself to investigate later, my name starts with A and my address book has this as A for some reason. Please ignore... or feel

Re: [music-dsp] Did anybody here think about signal integrity

Also a good starting place for beginners are the xiph show-and-tell videos (probably been posted here before, but whatever): https://xiph.org/video/vid2.shtml E On Wed, Jun 3, 2015 at 3:05 PM, Ethan Duni ethan.d...@gmail.com wrote: Perfect sinusoids/square waves/etc. only exist

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