Nonlinear spline adaptive filtering

Authors:
Michele Scarpiniti;Danilo Comminiello;Raffaele Parisi;Aurelio Uncini
Affiliations:
Department of Information Engineering, Electronics and Telecommunications (DIET) "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy;Department of Information Engineering, Electronics and Telecommunications (DIET) "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy;Department of Information Engineering, Electronics and Telecommunications (DIET) "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy;Department of Information Engineering, Electronics and Telecommunications (DIET) "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy
Venue:
Signal Processing
Year:
2013

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Abstract

In this paper a new class of nonlinear adaptive filters, consisting of a linear combiner followed by a flexible memory-less function, is presented. The nonlinear function involved in the adaptation process is based on a spline function that can be modified during learning. The spline control points are adaptively changed using gradient-based techniques. B-splines and Catmull-Rom splines are used, because they allow to impose simple constraints on control parameters. This new kind of adaptive function is then applied to the output of a linear adaptive filter and it is used for the identification of Wiener-type nonlinear systems. In addition, we derive a simple form of the adaptation algorithm and an upper bound on the choice of the step-size. Some experimental results are also presented to demonstrate the effectiveness of the proposed method.