Skip to main content

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

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.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Romis Ribeiro de Faissol Attux.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

de Faissol Attux, R.R., Loiola, M.B., Suyama, R. et al. Blind Search for Optimal Wiener Equalizers Using an Artificial Immune Network Model. EURASIP J. Adv. Signal Process. 2003, 460216 (2003). https://doi.org/10.1155/S1110865703303014

Download citation

Keywords

  • blind equalization
  • constant modulus algorithm
  • evolutionary computation
  • artificial immune systems
  • immune network model