Comparison of convergence behavior of distributed evolutionary digital filters

Masahide Abe, Masayuki Kawamata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper proposes distributed evolutionary digital filters (EDFs). The EDF is an adaptive digital filter which is controlled by adaptive algorithm based on evolutionary computation. In the proposed method, a large population of the original EDF is divided into smaller subpopulations. Each sub-EDF has one subpopulation and executes the small-sized main loop of the original EDE. In addition, the distributed algorithm periodically selects promising individuals from each subpopulation. Then, they migrate to different subpopulations. Numerical examples show that the distributed EDF has a higher convergence rate and smaller steady-state value of the square error than the original one.

Original languageEnglish
Title of host publicationISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings
Pages729-732
Number of pages4
DOIs
Publication statusPublished - 2001
Event2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001 - Sydney, NSW, Australia
Duration: 2001 May 62001 May 9

Publication series

NameISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings
Volume2

Other

Other2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001
CountryAustralia
CitySydney, NSW
Period01/5/601/5/9

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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