• DocumentCode
    2555818
  • Title

    Multi-space Competitive DGA and its application to localization of multiple signal sources

  • Author

    Horio, K. ; Ishikawa, S. ; Misawa, H. ; Tokiwa, T. ; Yamakawa, T. ; Kubota, R.

  • Author_Institution
    Grad. Sch. of Life Sci. & Syst. Eng., Kyushu Inst. of Technol., Kitakyushu, Japan
  • fYear
    2010
  • fDate
    15-17 Dec. 2010
  • Firstpage
    617
  • Lastpage
    621
  • Abstract
    In this paper, a new optimization method, which is effective for the problem that the optimum solution should be searched in several solution spaces, is proposed. The proposed method is an extension of distributed genetic algorithm (DGA), in which each sub-population searches a solution in different space. Based on the competition between sub-populations, population sizes are adequately changed. The proposed method is applied to signal source localization, in which the number of sources is unknown, and simulation results show the effectiveness of the method.
  • Keywords
    electroencephalography; genetic algorithms; sensor placement; signal sources; DGA; distributed genetic algorithm; optimization; signal source localization; Annealing; Gallium; competition between sub-population; distributed genetic algorithm; multiple solution spaces;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-1-4244-7377-9
  • Type

    conf

  • DOI
    10.1109/NABIC.2010.5716378
  • Filename
    5716378