A kernel recursive minimum error entropy adaptive filter

The minimum error entropy, a currently useful alternative criterion, is widely adopted in the signal processing domain against impulsive noise. In this brief, we propose a novel algorithm to blend the advantages of both the kernel recursive least squares algorithm and the minimum error entropy crite...

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Veröffentlicht in:Signal processing Jg. 193; S. 108410
Hauptverfasser: Wang, Gang, Yang, Xinyue, Wu, Lei, Fu, Zhenting, Ma, Xiangjie, He, Yuanhang, Peng, Bei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.04.2022
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ISSN:0165-1684, 1872-7557
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Abstract The minimum error entropy, a currently useful alternative criterion, is widely adopted in the signal processing domain against impulsive noise. In this brief, we propose a novel algorithm to blend the advantages of both the kernel recursive least squares algorithm and the minimum error entropy criterion, called kernel recursive minimum error entropy algorithm. The proposed new algorithm achieves better recovery performance in predicting the Mackey–Glass time series, equalizing the nonlinear channel under heavy tailed alpha-stable environments and processing EEG data.
AbstractList The minimum error entropy, a currently useful alternative criterion, is widely adopted in the signal processing domain against impulsive noise. In this brief, we propose a novel algorithm to blend the advantages of both the kernel recursive least squares algorithm and the minimum error entropy criterion, called kernel recursive minimum error entropy algorithm. The proposed new algorithm achieves better recovery performance in predicting the Mackey–Glass time series, equalizing the nonlinear channel under heavy tailed alpha-stable environments and processing EEG data.
ArticleNumber 108410
Author Peng, Bei
Yang, Xinyue
He, Yuanhang
Wang, Gang
Ma, Xiangjie
Fu, Zhenting
Wu, Lei
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  surname: Fu
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  surname: Peng
  fullname: Peng, Bei
  email: beipeng@uestc.edu.cn
  organization: School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China
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Keywords Kernel adaptive filter (KAF)
Kernel recursive minimum error entropy (KRMEE)
Minimum error entropy (MEE)
Language English
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Snippet The minimum error entropy, a currently useful alternative criterion, is widely adopted in the signal processing domain against impulsive noise. In this brief,...
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StartPage 108410
SubjectTerms Kernel adaptive filter (KAF)
Kernel recursive minimum error entropy (KRMEE)
Minimum error entropy (MEE)
Title A kernel recursive minimum error entropy adaptive filter
URI https://dx.doi.org/10.1016/j.sigpro.2021.108410
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