Performance comparisons of three IIR structures for adaptive system identification based on genetic algorithms

X. Shao, G. Sun, William Kenneth Jenkins

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

1 Scopus citations

Abstract

Genetic Algorithms (GA's) are based on the principles of natural selection and natural genetics that originate in biology. The Genetic Algorithm (GA) has been used for IIR adaptive system identification to deal with its multimodal error surface. The Genetic Algorithm (GA) can perform well in many different IIR adaptive filter structures, while the Gradient Algorithm often does not perform well in these situations. This paper focuses on the performances of three different structures of IIR filters based on the conventional Genetic Algorithm (GA) and the more specialized Multi-Parents Genetic Algorithm (MPGA).

Original languageEnglish (US)
Title of host publicationConference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages231-235
Number of pages5
ISBN (Electronic)9781467385763
DOIs
StatePublished - Feb 26 2016
Event49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 8 2015Nov 11 2015

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2016-February
ISSN (Print)1058-6393

Other

Other49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/8/1511/11/15

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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    Shao, X., Sun, G., & Jenkins, W. K. (2016). Performance comparisons of three IIR structures for adaptive system identification based on genetic algorithms. In M. B. Matthews (Ed.), Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 (pp. 231-235). [7421120] (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2016-February). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2015.7421120