Sorry, I was thinking of one that Miller wrote that I saw sometime back.
I haven't actually looked at the one on extended. I will check it out.
Let's stay in touch about this. It sounds like a fun project.
happy new year
On 12/31/2014 02:11 PM, Alexandre Torres Porres wrote:
> Miller (being the author) would know better
But the [moog~] object that I see here on Pd extended was written by
gunter Geiger.
> it would be super cool to have this as a Pd
> abstraction rather than an extern.
Dan Wilcox also wanted that as I remember. If you care to help me we
could try and do it. I kinda suck at math and all but when I put my
mind into it I can do these things I never knew I could :) I've been
implementing several filters with [fexpr~] and/or vanilla's raw
pole/zero filters. I've kinda done them all, [moog~] is the next on my
list.
But I probably won't get into this until the 2nd half of january, as I
plan to go to some island for my summer break.
cheers and happy new year.
2014-12-31 19:42 GMT-02:00 David Medine <[email protected]
<mailto:[email protected]>>:
Cool, I will definitely check out this SC object. Thanks for that.
Miller (being the author) would know better than I of course, but
I believe the way that [moog~] works is to use Runge-Kutta to
solve the ordinary differential equation that governs each stage
of the filter in its continuous time representation. This equation
(along with a discrete implementation of the complete filter) is
what is described in the paper I mentioned. Incidentally, using
Runge-Kutta (or any appropriate iterative ODE solver) also
abnegates the frequency warping problem.
I think it might be very difficult to code this up with [fexpr~].
It would certainly require at least a quadrupling of the sampling
rate. Has anyone out there ever implemented Runge-Kutta with
[expr~]? It might also be that Pd's data structures are an
appropriate choice for such a project? Either way, it would be
super cool to have this as a Pd abstraction rather than an extern.
-David
On 12/31/2014 10:05 AM, Alexandre Torres Porres wrote:
Hi David,
> It'd certainly be interesting to see an what actual implementation
> of this does, rather than just some matlab plots.
An actual implementation is provided in the MoogFF filter in
Super Collider, you can just download and try it out. The code of
the object is also provided somewhere, as it is a source code.
I'd like to understand pd's [moog~] object one day, and implement
it with [fexpr~] or something. Maybe I'll do this other one as well.
Cheers
2014-12-29 17:20 GMT-02:00 David Medine <[email protected]
<mailto:[email protected]>>:
I believe, though I may be wrong, that the Moog vcf object is
based on the algorithm described in the 2004 Huovalainen
paper (citation [6] in the Fontana):
http://www.mirlab.org/conference_papers/International_Conference/DAFx%202004/Proc/P_061.pdf
I am a little confused here (in the Fontana) by the author's
assertion that he can implement a 'delay-free' loop by
computing the output first, and then finding the states of
the filter based on this. I don't quite see how this is
different from finding the states first and then finding the
output -- chicken then the egg vs. egg then the chicken.
Still, judging by the plots they provide, they seem to have
overcome the frequency warping issue (an artifact of unit
delay) described by Huovalainen.
It'd certainly be interesting to see an what actual
implementation of this does, rather than just some matlab plots.
-David
On 12/28/2014 07:43 PM, Alexandre Torres Porres wrote:
hi, do you know if the moog object comes from this paper?
http://quod.lib.umich.edu/cgi/p/pod/dod-idx/preserving-the-structure-of-the-moog-vcf-in-the-digital.pdf?c=icmc;idno=bbp2372.2007.062
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