Asynchronous and stochastic dimension updating PSO and its application to parameter estimation for frequency modulated (FM) sound waves

Yanxia Sun, Zenghui Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

The particle velocity and position updating play very important roles for achieving good optimization performance of Particle Swarm Optimization (PSO). This paper analyzed the performance of asynchronously updating PSO and synchronously updating PSO by simulation and discovered that the asynchronously updating way can achieve better optimization performance than the synchronously updating way. Moreover, the convergence rate of asynchronously PSO is faster than that of synchronously PSO, which means that there is spare time to achieve better optimization performance based on certain techniques. Here we proposed a stochastic dimension updating technique in which only some dimensions of position will be updated. Several benchmark functions have been used to validate the proposed method. The proposed method is also applied to the parameter estimation for frequency modulated sound waves.

Original languageEnglish
Title of host publicationProceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015
EditorsLiang Xiao, Yinglin Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages583-587
Number of pages5
ISBN (Electronic)9781467380867
DOIs
Publication statusPublished - 10 Jun 2016
Event3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015 - Nanjing, China
Duration: 18 Dec 201520 Dec 2015

Publication series

NameProceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015

Conference

Conference3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015
Country/TerritoryChina
CityNanjing
Period18/12/1520/12/15

Keywords

  • Particle swarm optimization
  • asynchronous updating
  • parameter estimation
  • stochastic dimension updating

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems

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