Stability analysis of adaptive filters with regression vector nonlinearities

Authors:
Leonardo Rey Vega;Hernan Rey;Jacob Benesty
Affiliations:
Universidad de Buenos Aires and CONICET, Buenos Aires, Argentina;Universidad de Buenos Aires and CONICET, Buenos Aires, Argentina;INRS-EMT, Université du Québec, Montréal, Québec, Canada H5A 1K6
Venue:
Signal Processing
Year:
2011

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Abstract

We present a unified framework to analyze the mean and mean-square stability of a large class of adaptive filters. We do this without obtaining a full transient model, allowing us to acquire sufficient conditions on the stability without assuming a given statistical distribution for the input regressors. We also apply the proposed framework to some popular adaptive filtering schemes, showing that in some cases the sufficient conditions derived are very tight and even necessary too.