Open Access

Blind Search for Optimal Wiener Equalizers Using an Artificial Immune Network Model

  • Romis Ribeiro de Faissol Attux1Email author,
  • Murilo Bellezoni Loiola1,
  • Ricardo Suyama1,
  • Leandro Nunes de Castro2,
  • Fernando José Von Zuben2 and
  • João Marcos Travassos Romano1
EURASIP Journal on Advances in Signal Processing20032003:460216

Received: 28 June 2002

Published: 21 July 2003


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.


blind equalizationconstant modulus algorithmevolutionary computationartificial immune systemsimmune network model

Authors’ Affiliations

DSPCOM, DECOM, FEEC, State University of Campinas
DCA, FEEC, State University of Campinas


© Copyright © 2003 Hindawi Publishing Corporation 2003