Please use this identifier to cite or link to this item:
Type: Artigo de periódico
Title: Blind search for optimal Wiener equalizers using an artificial immune network model
Author: Attux, RRD
Loiola, MB
Suyama, R
de Castro, LN
Von Zuben, FJ
Romano, JMT
Abstract: This work proposes a framework to determine the optimal Wiener equalizer by using an artificial immune network model together with the constant modulus (CM) cost function. This study was primarily motivated by recent theoretical results concerning the CM criterion and its relation to the Wiener approach. The proposed immune-based technique was tested under different channel models and filter orders, and benchmarked against a procedure using a genetic algorithm with niching. The results demonstrated that the proposed strategy has a clear superiority when compared with the more traditional technique. The proposed algorithm presents interesting features from the perspective of multimodal search, being capable of determining the optimal Wiener equalizer in most runs for all tested channels.
Subject: blind equalization
constant modulus algorithm
evolutionary computation
artificial immune systems
immune network model
Country: EUA
Editor: Hindawi Publishing Corporation
Rights: aberto
Date Issue: 2003
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

Files in This Item:
File Description SizeFormat 
WOS000184992900003.pdf1.41 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.