Adaptive filtering based on extended kernel recursive maximum correntropy
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.