Kernel Adaptive Filters With Feedback Based on Maximum Correntropy

Kernel Adaptive Filters With Feedback Based on Maximum Correntropy

This paper presents novel kernel adaptive filters with feedback, namely, kernel recursive maximum correntropy with multiple feedback (KRMC-MF) and its simplified version, a linear recurrent kernel online learning algorithm based on maximum correntropy criterion (LRKOL-MCC). In LRKOL-MCC and KRMC-MF,...

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Bibliographic Details
Main Authors: Shiyuan Wang, Lujuan Dang, Wanli Wang, Guobing Qian, Chi K. Tse
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Kernel adaptive filters
maximum correntropy
minimum mean square error
feedback structure
convergence
Online Access:https://ieeexplore.ieee.org/document/8295208/

Internet

https://ieeexplore.ieee.org/document/8295208/

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