Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/96024
Type: Artigo de evento
Title: Self-learning Deconvolution Using A Cascade Of Magnitude And Phase Equalizers
Author: da Rocha Carlos A.F.
Romano Joao Marcos T.
Macchi Odile
Abstract: In this work, we propose a non-linear structure for self-learning equalization, which can be easily updated using the direct-decision error criterion. Such a structure consists in three different systems: an IIR predictor that provides the magnitude equalization, an automatic gain control and a non-linear phase equalizer. The paper presents a theoretical analysis for the proposed structure and some simulation results with severe channels.
Editor: IEEE, Piscataway, NJ, United States
Rights: fechado
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0029453460&partnerID=40&md5=f95dc71611b06c67951d9d2573eb2c92
Date Issue: 1995
Appears in Collections:Unicamp - Artigos e Outros Documentos

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