1. Convex regularized recursive maximum correntropy algorithm.
- Author
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Zhang, Xie, Li, Kaixin, Wu, Zongze, Fu, Yuli, Zhao, Haiquan, and Chen, Badong
- Subjects
- *
ADAPTIVE filters , *LEAST squares , *ROBUST control , *RECURSIVE functions , *ALGORITHMS - Abstract
In this brief, a robust and sparse recursive adaptive filtering algorithm, called convex regularized recursive maximum correntropy (CR-RMC), is derived by adding a general convex regularization penalty term to the maximum correntropy criterion (MCC). An approximate expression for automatically selecting the regularization parameter is also introduced. Simulation results show that the CR-RMC can significantly outperform the original recursive maximum correntropy (RMC) algorithm especially when the underlying system is very sparse. Compared with the convex regularized recursive least squares (CR-RLS) algorithm, the new algorithm also shows strong robustness against impulsive noise. The CR-RMC also performs much better than other LMS-type sparse adaptive filtering algorithms based on MCC. [ABSTRACT FROM AUTHOR]
- Published
- 2016
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