Yes, I see....the signal with compact support can have zeros outside
of ROC...It's clear why, now. I'm not sure what to do differently
yet....
my idea was this: given alpha <=1 (an adaptation coefficient)
we do:
1. Fourier transform of 3 things: reference signal (length 2N),
received signal from microphone (length 2N), and the weights (length
N, padded with N zeros at the end).
2. divide (FT of reference) by (FT of received)
3. unwrap phase; take result of (2) as phase and magnitude
4. multiply (FT of weights) by mag^alpha*( cos (phase*alpha) + i
sin(phase*alpha) )
5. take IFT of weights, and throw away final N samples
Maybe there's an eigenvalue/vector trick that I'm missing...
chuck
On 4/8/06, Piotr Majdak <piotr(a)majdak.com> wrote:
> Hi Charles,
>
> Charles Henry wrote:
>
> >2. Fourier deconvolution: The only restriction here is that the
> >signal spans the entire frequency range (which in terms of wavelets,
> >is just an octave chirp).
> >
> Dividing by a spectrum, every zero become a pole. Thus, dividing by a
> spectrum of a signal with zeros outside of ROC will result in unstable
> signals. To avoid this problem you can try to calculate a minimum phase
> version of your ref-signal and divide by that one. Of course, the phase
> information won't be deconvolved perfectly in this case :-(
>
> br, Piotr Majdak
>
--
Charles Zachary Henry
anti.dazed.med
Med student who needs a Mickey's