Kernel recursive maximum correntropy

Zongze Wu 1 , Jiahao Shi 1 , Xie Zhang 1 , Wentao Ma 2 , Badong Chen 2* , Senior Member, IEEE 1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, China 2. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China * Fax: 86-29-82668672,Tel:86-29-82668802 ext. 8009, [email protected] Abstract—In this letter, a robust kernel adaptive algorithm, called the kernel recursive maximum correntropy (KRMC), is derived in kernel space and under the maximum correntropy criterion (MCC). The proposed algorithm is particularly useful for nonlinear and non-Gaussian signal processing, especially when data contain large outliers or disturbed by impulsive noises. The superior performance of KRMC is confirmed by simulation results about short-term chaotic time series prediction in alpha-stable noise environments.