This article is part of the series Nonlinear Signal and Image Processing - Part II.

Open Access Research Article

Learning Rate Updating Methods Applied to Adaptive Fuzzy Equalizers for Broadband Power Line Communications

Moisés V Ribeiro

Author Affiliations

Department of Communications, State University of Campinas, São Paulo 13083970 , Brazil

EURASIP Journal on Advances in Signal Processing 2004, 2004:824326  doi:10.1155/S1110865704407021


The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2004/16/824326


Received: 1 September 2003
Revisions received: 31 May 2004
Published: 2 December 2004

© 2004 Ribeiro

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.

Keywords:
power line communications; broadband applications; nonlinear equalization; fuzzy systems; learning rate updating; impulse noises

Research Article