• DocumentCode
    2638724
  • Title

    Hardware design of self-organization for clustering

  • Author

    Ishihara, Atsushi ; Maeda, Yutaka

  • Author_Institution
    Kansai Univ., Suita
  • fYear
    2007
  • fDate
    17-20 Sept. 2007
  • Firstpage
    1035
  • Lastpage
    1038
  • Abstract
    In this paper, we design a self-organization network to classify groups. Using histogram based on outputs of a network, we establish a proper evaluation function defined by the distance between the highest class and the second highest class. Maximizing the evaluation gives proper network. Basic design of this classification network system for FPGA is described. Details of the design are explained. Some simulation results will be shown.
  • Keywords
    field programmable gate arrays; hardware description languages; logic design; pattern classification; pattern clustering; self-organising feature maps; statistical analysis; FPGA; classification network system; hardware design; histogram; pattern clustering; self-organization network; Design engineering; Education; Electronic mail; Field programmable gate arrays; Histograms; Multi-layer neural network; Neural network hardware; Neural networks; Statistical analysis; Supervised learning; clustering; hardware implementation; neural networks; self-organization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE, 2007 Annual Conference
  • Conference_Location
    Takamatsu
  • Print_ISBN
    978-4-907764-27-2
  • Electronic_ISBN
    978-4-907764-27-2
  • Type

    conf

  • DOI
    10.1109/SICE.2007.4421136
  • Filename
    4421136