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:
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@majdak.com wrote:
Hi Charles,
Charles Henry wrote:
- 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