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A complex adaptive algorithm for IIR filtering

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1 Author(s)
Shynk, J.J. ; Stanford University, Stanford, CA, USA

This correspondence generalizes the Gauss-Newton algorithm [1] for adaptive IIR filters to include complex coefficients. The resulting algorithm simultaneously updates the real and imaginary parts of the filter coefficients to minimize the average squared estimation error. It has application in frequency-domain adaptive IIR filtering [2] where the signals and filter coefficients are complex.

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Acoustics, Speech and Signal Processing, IEEE Transactions on  (Volume:34 ,  Issue: 5 )