The most essentially flat signal is a delta function or impulse, which is also phase-aligned. Apply any all-pass filter or series thereof to the impulse, and the fourier transform over infinite time will remain flat. I recommend investigating Schroeder filters.
– Evan Balster creator of imitone <http://imitone.com> On Sat, Jul 30, 2016 at 5:39 PM, gm <g...@voxangelica.net> wrote: > I think it's interesting for instance for early echoes in a reverb. > For longer sequences it seems to become very self-similar? > > I only looked into the thing under "Additive recurrence", the rest is > totally above my head, and played around with this a little bit, since it's > basically a random number generator with "bad parameters" there. > I tried similar things before with the golden ratio, bascially even the > same thing I just realize. > Like panning in a seemingly random fashion with golden ratio mod 1. > > With little sucess in reverbs, though, for instance most of the time it's > not a great > idea to just tune delay lengths to golden ratios... > > But maybe it's useful for setting delay lengths in a different way? > > Just seeing the similarity between a classical reverb algorithm and random > number generators > with the feedback loop acting as mod operator.. didn't see it like that > before > > Did anybody build a reverb based on a random generator algorithm? > Or are reverbs just that and it just never occured to me? > > What I also wonder is the difference between a sequence like that (or any > random sequence) > and a sequence thats synthesized with FFT to be flat but with random > phases. > I wonder what's better in terms of what and why, when it comes to reverb > and/or convolution, > > > > Am 30.07.2016 um 19:57 schrieb Patric Schmitz: > >> Hi, >> >> On 07/28/2016 08:43 PM, gm wrote: >> >>> My problem was that a short segment of random isn't spectrally >>> straigh-line flat. >>> >> On 07/30/2016 07:22 PM, gm wrote: >> >>> Just a short sequence of random numbers really exhibits large >>> formant like fluctuations . >>> >> I tried following this discussion even though, admittedly, most >> of it is way over my head. Still, I wonder if the problem of >> short random sample sets being too non-uniformly distributed >> could be alleviated somehow, by not using white noise for the >> samples, but what they call a low-discrepancy quasi- or subrandom >> sequence of numbers. >> >>> https://en.wikipedia.org/wiki/Low-discrepancy_sequence >>> >> I heard about them in a different context, and it seems their >> main property is that they converge against the equally >> distributed limit distribution much quicker than true random >> samples taken from that distribution. Maybe they could be useful >> here to get a spectrally more flat distribution with a fewer >> number of samples? >> >> As said, I'm by far no expert in the field and most of what has >> been said is above my level of understanding, so please feel free >> to discard this as utter nonsense! >> >> Best regards, >> Patric Schmitz >> _______________________________________________ >> dupswapdrop: music-dsp mailing list >> music-dsp@music.columbia.edu >> https://lists.columbia.edu/mailman/listinfo/music-dsp >> >> > _______________________________________________ > dupswapdrop: music-dsp mailing list > music-dsp@music.columbia.edu > https://lists.columbia.edu/mailman/listinfo/music-dsp > >
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