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? Now that I think about it, another application might be in stereo imaging. Start with a mono signal, generate the Hilbert pair, feed one to each ear. Now you've got a really wide image without changing the sound much at all. -Ethan On Tue, Feb 7, 2017 at 9:20 AM, Theo Verelst <theo...@theover.org> wrote: > Like with many transforms, I can't help but practically think that it's > hard to make a tradeoff between the meaning of the results, such as > frequency and amplitude, some rough estimate of the normally obtained > accuracy (can you send a CD signal through the DSP stuff, invert back to > audio samples and find the inverse transform still worth listening to ?), > and whether you're going to get a measurement that sticks data to certain > implicit vectors while believing all measurements are accurate. > > I like the idea of an IIR filter for frequency analysis, or a bank of them > with dyadic structure, and some smart interpreter of the measurement > results, or even an adaptive systematic to very accurately discern between > frequency, time axis or envelope ("amplitude change", or maybe congruence > with natural e-powers) from for instance an accurately recorded piano tone. > It's hard to get as accurate as I would like when you include signal > reconstruction in the picture, maybe if you take relatively high sampling > frequency. > > Theo V. > > _______________________________________________ > dupswapdrop: music-dsp mailing list > music-dsp@music.columbia.edu > https://lists.columbia.edu/mailman/listinfo/music-dsp > >
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