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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Autores principales: Shiyuan Wang, Lujuan Dang, Wanli Wang, Guobing Qian, Chi K. Tse
Formato: article
Lenguaje:EN
Publicado: IEEE 2018
Materias:
Kernel adaptive filters
maximum correntropy
minimum mean square error
feedback structure
convergence
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Acceso en línea:https://doaj.org/article/5751cd9eb4e14107834ee836091e3196
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https://doaj.org/article/5751cd9eb4e14107834ee836091e3196

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