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

dc.creatorRibeiro, MV
dc.date2004
dc.date42309
dc.date2014-11-18T03:40:40Z
dc.date2015-11-26T16:50:29Z
dc.date2014-11-18T03:40:40Z
dc.date2015-11-26T16:50:29Z
dc.date.accessioned2018-03-28T23:37:14Z
dc.date.available2018-03-28T23:37:14Z
dc.identifierEurasip Journal On Applied Signal Processing. Hindawi Publishing Corporation, v. 2004, n. 16, n. 2592, n. 2599, 2004.
dc.identifier1110-8657
dc.identifierWOS:000227366300019
dc.identifier10.1155/S1110865704407021
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/80823
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/80823
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/80823
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1275737
dc.descriptionThis 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.
dc.description2004
dc.description16
dc.description2592
dc.description2599
dc.languageen
dc.publisherHindawi Publishing Corporation
dc.publisherSylvania
dc.publisherEUA
dc.relationEurasip Journal On Applied Signal Processing
dc.relationEURASIP J Appl. Signal Process.
dc.rightsaberto
dc.sourceWeb of Science
dc.subjectpower line communications
dc.subjectbroadband applications
dc.subjectnonlinear equalization
dc.subjectfuzzy systems
dc.subjectlearning rate updating
dc.subjectimpulse noises
dc.subjectBayesian Equalizer
dc.subjectRate Adaptation
dc.subjectChannels
dc.subjectConvergence
dc.subjectFilters
dc.subjectNoise
dc.titleLearning rate updating methods applied to adaptive fuzzy equalizers for broadband power line communications
dc.typeArtículos de revistas


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