On the performance comparison of gradient-type joint process estimators in adaptive signal processing

Abstract

In adaptive signal processing, joint process estimation plays an important role in various estimation problems. It is well known that a joint process estimator consists of two structures, namely the orthogonalizer and the regression filter. In literature, orthogonalization step is performed either by orthogonal transformations or by linear predictors. While… (More)

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