Re: DFT and resonance -- question

Thanks, Rune. OK, I'm looking for human-ear-type resolution, so if in
1/10th of a sec I can get resolution of 10 hZ around A (440 hZ), that's
perfect, since A#/Bb isn't until about 477 hZ.

Maybe I'm naive, but I'm not so worried about the overtones, because
they should appear quite clearly and dinstinctly, no? (As long as we're
talking just a few simultaneous notes such as in a piano sonata...I'm
not expecting a crystal-clear visual rendition of pitches in heavy
metal!!!) And other noise (cymbals, drums, hiss, etc.) should appear as
a continuous range of frequencies. I just want to be able to pick out
individual instrument/voice tones and overtones, and be able to clearly
see what pitch of the 12-tone scale they are. They can be along a
background of noise, that's fine, just as long as the pitches of a few
instruments stand out visually in the final spectogram, with
*identifiable* pitches--A, Bb, C, C#, etc...

If the algorithm I described, of a filterbank with freq separation of,
say, 10 hZ between bands (although like I said, the width of each band
will overlap with the next, right?) picks up a 'blurred' image of the
spectrum, then deconvolution should work to 'tighten up' the
frequencies, just as one turns a blurry astronomical image into a clear
one. This is based on the assumption that everything is generated by
sines, so it will clean up the sines (piano fundamental, clarinet,
etc), but cymbal crashes, noise, etc. will be left largely unchanged
(which is fine!).

So *is* there a spectrum analyzer out there that performs this
deconvolution step? Is there somewhere that explains exactly how to
apply this deconvolution? I don't want to reinvent the wheel... Or is a
10hZ-resolution band perfectly reasonable, no deconvolution necessary,
but for some reason it doesn't work well when done via FFT?

.

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