>> Fourier would be proud.
>> (SFT strikes again :-) )

> I'm not sure what your point is.

Sorry! That wasn't meant to be a criticism.
Just noting the "classic" approach as opposed to the 'throw an FFT at
it' approach.
A nice choice.

> I'm assuming SFT is supposed to mean Slow  Fourier Transform

Yes.

>, as apposed to FFT (Fast Fourier Transform)? =A0Do you see a
> way to apply the FFT algorithm to checking for the existence of a few kno=
wn
> frequencies that aren't in a nice evenly spaced progression?

Possibly yes, or one of the arcane variants of it - but that wasn't my aim.
Hmm - deep memory or random firing neuron suggests Winograd transform.
Gargoyles - nope - addition biased method.

WikiP suggests Guo & Burns, Shentov and Edelman (Sparse and
approximate) - and I'll happily admit to having heard of none of them
before.

Long long ago I played with optimising in place butterflies for use on
VERY limited memory VERY slow processors (not my actual project) but
nowadays I'd be as likely to accidentally end up with a Lorentz
Butterfly as a Tukey one.

Hours of fun -

        http://en.wikipedia.org/wiki/Fast_Fourier_transform

  Russell

-- =

http://www.piclist.com PIC/SX FAQ & list archive
View/change your membership options at
http://mailman.mit.edu/mailman/listinfo/piclist