Title of Paper:Adaptive Filtering Based on Extended Kernel Recursive Maximum Correntropy

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Date of Publication:2017-01-01

Included Journals:EI、CPCI-S、Scopus

Volume:2017-May

Page Number:2716-2722

Key Words:Adaptive filtering; alpha-stable noise; maximum correntropy; nonlinear system; recursive least squares; time-variant

Abstract:In this paper, an adaptive filtering algorithm, termed the extended kernel recursive maximum correntropy (EX-KRMC) algorithm is proposed as a novel approach of traditional recursion based adaptive filtering algorithms. Maximum correntropy criterion is employed to better the robustness to non-Gaussian noise and kernel methods are used to enable the capacity for nonlinear systems. It is verified by simulation experiments that EX-KRMC outperforms existing adaptive filtering algorithms when dealing with non-Gaussian noise for nonlinear time-variant systems.