Robust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion

Entropy

Zongze Wu²  Siyuan Peng²  Badong Chen¹  Haiquan Zhao³ 

[1]School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China

[2]School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510640, China

[3] E-Mails:

[4]School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China

[5] E-Mail:

关键词: Hammerstein adaptive filtering;    MCC;    nonlinear system identification;   

DOI  :  10.3390/e17107149

来源: mdpi

【 摘 要 】

The maximum correntropy criterion (MCC) has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers. In this work, we apply the MCC criterion to develop a robust Hammerstein adaptive filter. Compared with the traditional Hammerstein adaptive filters, which are usually derived based on the well-known mean square error (MSE) criterion, the proposed algorithm can achieve better convergence performance especially in the presence of impulsive non-Gaussian (e.g., α-stable) noises. Additionally, some theoretical results concerning the convergence behavior are also obtained. Simulation examples are presented to confirm the superior performance of the new algorithm.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.