Nonlinear spline adaptive filtering

作者：Scarpiniti Michele^*; Comminiello Danilo; Parisi Raffaele; Uncini Aurelio

来源：Signal Processing, 2013, 93(4): 772-783.

DOI：10.1016/j.sigpro.2012.09.021

• Spline adaptive filter
• Nonlinear adaptive filter
• Nonlinear FIR filter
• Wiener system identification

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.

• 出版日期2013-4