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发布时间：2019-03-12

论文类型：会议论文

发表时间：2017-01-01

收录刊物：Scopus、CPCI-S、EI

卷号：2017-May

页面范围：2716-2722

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

摘要：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.