System identification techniques for adaptive signal processing

Many problems in adaptive filtering can be approached from the point of view of system identification. The close interconnection between these two disciplines is explored in some detail. This approach makes it possible to apply recursive parameter estimation algorithms to adaptive signal processing. Several examples are discussed including: adaptive line enhancement, generalized adaptive noise cancelling, adaptive deconvolution and adaptive TDOA estimation. It is shown how the recursive maximum likelihood algorithm can be used for both FIR and IIR filtering, and some preliminary results are presented. Several alternative algorithms are briefly discussed.

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