Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/80823
Type: Artigo de periódico
Title: Learning rate updating methods applied to adaptive fuzzy equalizers for broadband power line communications
Author: Ribeiro, MV
Abstract: This paper introduces adaptive fuzzy equalizers with variable step size for broadband power line (PL) communications. Based on delta-bar-delta and local Lipschitz estimation updating rules, feedforward, and decision feedback approaches, we propose singleton and nonsingleton fuzzy equalizers with variable step size to cope with the intersymbol interference (ISI) effects of PL channels and the hardness of the impulse noises generated by appliances and nonlinear loads connected to low-voltage power grids. The computed results show that the convergence rates of the proposed equalizers are higher than the ones attained by the traditional adaptive fuzzy equalizers introduced by J. M. Mendel and his students. Additionally, some interesting BER curves reveal that the proposed techniques are efficient for mitigating the above-mentioned impairments.
Subject: power line communications
broadband applications
nonlinear equalization
fuzzy systems
learning rate updating
impulse noises
Country: EUA
Editor: Hindawi Publishing Corporation
Rights: aberto
Identifier DOI: 10.1155/S1110865704407021
Date Issue: 2004
Appears in Collections:Unicamp - Artigos e Outros Documentos

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