A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel Equalization

A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel Equalization

In this paper, a kernel recursive maximum Versoria-like criterion (KRMVLC) algorithm has been constructed, derived, and analyzed within the framework of nonlinear adaptive filtering (AF), which considers the benefits of logarithmic second-order errors and the symmetry maximum-Versoria criterion (MVC...

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Main Authors: Qishuai Wu, Yingsong Li, Wei Xue
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Symmetry
Subjects:
kernel recursive maximum Versoria-like criterion
maximum Versoria criterion
nonlinear channel equalization
Online Access:https://www.mdpi.com/2073-8994/11/9/1067
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spelling doaj-4dc793ec3c674e60a1247142ea654cc92020-11-25T02:20:26ZengMDPI AGSymmetry2073-89942019-08-01119106710.3390/sym11091067sym11091067A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel EqualizationQishuai Wu0Yingsong Li1Wei Xue2College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaIn this paper, a kernel recursive maximum Versoria-like criterion (KRMVLC) algorithm has been constructed, derived, and analyzed within the framework of nonlinear adaptive filtering (AF), which considers the benefits of logarithmic second-order errors and the symmetry maximum-Versoria criterion (MVC) lying in reproducing the kernel Hilbert space (RKHS). In the devised KRMVLC, the Versoria approach aims to resist the impulse noise. The proposed KRMVLC algorithm was carefully derived for taking the nonlinear channel equalization (NCE) under different non-Gaussian interferences. The achieved results verify that the KRMVLC is robust against non-Gaussian interferences and performs better than those of the popular kernel AF algorithms, like the kernel least-mean-square (KLMS), kernel least-mixed-mean-square (KLMMN), and Kernel maximum Versoria criterion (KMVC).https://www.mdpi.com/2073-8994/11/9/1067kernel recursive maximum Versoria-like criterionmaximum Versoria criterionnonlinear channel equalization
collection DOAJ
language English
format Article
sources DOAJ
author Qishuai Wu
Yingsong Li
Wei Xue
spellingShingle Qishuai Wu
Yingsong Li
Wei Xue
A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel Equalization
Symmetry
kernel recursive maximum Versoria-like criterion
maximum Versoria criterion
nonlinear channel equalization
author_facet Qishuai Wu
Yingsong Li
Wei Xue
author_sort Qishuai Wu
title A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel Equalization
title_short A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel Equalization
title_full A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel Equalization
title_fullStr A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel Equalization
title_full_unstemmed A Kernel Recursive Maximum Versoria-Like Criterion Algorithm for Nonlinear Channel Equalization
title_sort kernel recursive maximum versoria-like criterion algorithm for nonlinear channel equalization
publisher MDPI AG
series Symmetry
issn 2073-8994
publishDate 2019-08-01
description In this paper, a kernel recursive maximum Versoria-like criterion (KRMVLC) algorithm has been constructed, derived, and analyzed within the framework of nonlinear adaptive filtering (AF), which considers the benefits of logarithmic second-order errors and the symmetry maximum-Versoria criterion (MVC) lying in reproducing the kernel Hilbert space (RKHS). In the devised KRMVLC, the Versoria approach aims to resist the impulse noise. The proposed KRMVLC algorithm was carefully derived for taking the nonlinear channel equalization (NCE) under different non-Gaussian interferences. The achieved results verify that the KRMVLC is robust against non-Gaussian interferences and performs better than those of the popular kernel AF algorithms, like the kernel least-mean-square (KLMS), kernel least-mixed-mean-square (KLMMN), and Kernel maximum Versoria criterion (KMVC).
topic kernel recursive maximum Versoria-like criterion
maximum Versoria criterion
nonlinear channel equalization
url https://www.mdpi.com/2073-8994/11/9/1067
work_keys_str_mv AT qishuaiwu akernelrecursivemaximumversorialikecriterionalgorithmfornonlinearchannelequalization
AT yingsongli akernelrecursivemaximumversorialikecriterionalgorithmfornonlinearchannelequalization
AT weixue akernelrecursivemaximumversorialikecriterionalgorithmfornonlinearchannelequalization
AT qishuaiwu kernelrecursivemaximumversorialikecriterionalgorithmfornonlinearchannelequalization
AT yingsongli kernelrecursivemaximumversorialikecriterionalgorithmfornonlinearchannelequalization
AT weixue kernelrecursivemaximumversorialikecriterionalgorithmfornonlinearchannelequalization
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