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.
>
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