Robust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion

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 H...

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Bibliographic Details
Main Authors: Zongze Wu, Siyuan Peng, Badong Chen, Haiquan Zhao
Format: Article
Language:English
Published: MDPI AG 2015-10-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/17/10/7149
Description
Summary: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.
ISSN:1099-4300