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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Learning rate updating methods applied to adaptive fuzzy equalizers for broadband power line communications

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Author(s):
Ribeiro, Moisés Vidal
Total Authors: 1
Document type: Journal article
Source: EURASIP Journal on Advances in Signal Processing; v. 16, p. 2592-2599, Nov. 2004.
Field of knowledge: Engineering - Electrical Engineering
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. (AU)

FAPESP's process: 02/12216-3 - Advanced signal processing techniques on telecommunications: desconvolution and identification
Grantee:João Marcos Travassos Romano
Support Opportunities: Research Projects - Thematic Grants