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.

[1]  Nanning Zheng,et al.  Steady-State Mean-Square Error Analysis for Adaptive Filtering under the Maximum Correntropy Criterion , 2014, IEEE Signal Processing Letters.

[2]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[3]  Nanning Zheng,et al.  Generalized Correntropy for Robust Adaptive Filtering , 2015, IEEE Transactions on Signal Processing.

[4]  Weifeng Liu,et al.  The Kernel Least-Mean-Square Algorithm , 2008, IEEE Transactions on Signal Processing.

[5]  S. Thomas Alexander,et al.  Adaptive Signal Processing , 1986, Texts and Monographs in Computer Science.

[6]  C. L. Nikias,et al.  Signal processing with fractional lower order moments: stable processes and their applications , 1993, Proc. IEEE.

[7]  Badong Chen,et al.  Kernel adaptive filtering with maximum correntropy criterion , 2011, The 2011 International Joint Conference on Neural Networks.

[8]  Shie Mannor,et al.  The kernel recursive least-squares algorithm , 2004, IEEE Transactions on Signal Processing.

[9]  Shing-Chow Chan,et al.  A recursive least M-estimate algorithm for robust adaptive filtering in impulsive noise: fast algorithm and convergence performance analysis , 2004, IEEE Transactions on Signal Processing.

[10]  Weifeng Liu,et al.  Extended Kernel Recursive Least Squares Algorithm , 2009, IEEE Transactions on Signal Processing.

[11]  Tianshuang Qiu,et al.  The Equivalency of Minimum Error Entropy Criterion and Minimum Dispersion Criterion for Symmetric Stable Signal Processing , 2010, IEEE Signal Processing Letters.

[12]  J. Weng,et al.  Adaptive nonlinear RLS algorithm for robust filtering in impulse noise , 1997, Proceedings of 1997 IEEE International Symposium on Circuits and Systems. Circuits and Systems in the Information Age ISCAS '97.

[13]  James R. Zeidler,et al.  Adaptive tracking of linear time-variant systems by extended RLS algorithms , 1997, IEEE Trans. Signal Process..

[14]  Zongze Wu,et al.  Kernel recursive maximum correntropy , 2015, Signal Process..

[15]  José Carlos Príncipe,et al.  Using Correntropy as a cost function in linear adaptive filters , 2009, 2009 International Joint Conference on Neural Networks.

[16]  Tian-shuang Qiu,et al.  A new correntropy based TDE method under α-stable distribution noise environment , 2011 .

[17]  T. Ng,et al.  A recursive least M-estimate (RLM) adaptive filter for robust filtering in impulse noise , 2000, IEEE Signal Processing Letters.

[18]  Don H. Johnson,et al.  Statistical Signal Processing , 2009, Encyclopedia of Biometrics.