Author： Wu Zongze Peng Siyuan Chen Badong Zhao Haiquan
Publisher： MDPI
E-ISSN： 1099-4300|17|10|7149-7166
ISSN： 1099-4300
Source： Entropy, Vol.17, Iss.10, 2015-10, pp. : 7149-7166
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
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.
Related content
Access to resources
Recommend
Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images
By Zhao Haiying Liu Yong Xie Xiaojia Liao Yiyi Liu Xixi
Sensors, Vol. 16, Iss. 7, 2016-07 ,pp. :
Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation
By Liu Xi Qu Hua Zhao Jihong Yue Pengcheng Wang Meng
Sensors, Vol. 16, Iss. 9, 2016-09 ,pp. :
Adaptive Filtering Queueing for Improving Fairness
By Yang Jui-Pin
Applied Sciences, Vol. 5, Iss. 2, 2015-06 ,pp. :