• DocumentCode
    314407
  • Title

    Multiple categorization using fuzzy ART

  • Author

    Lavoie, Pierre ; Crespo, Jean-François ; Savaria, Yvon

  • Author_Institution
    Defence Res. Establ., Ottawa, Ont., Canada
  • Volume
    3
  • fYear
    1997
  • fDate
    9-12 Jun 1997
  • Firstpage
    1983
  • Abstract
    The internal competition between categories in the fuzzy adaptive resonance theory (ART) neural model can be biased by replacing the original choice function with one that contains a tuning parameter under external control. The competition can be biased, so that, for example, categories of a desired size can be favored. This attentional tuning mechanism allows recalling for a same input different categories under different circumstances, even when no additional learning tabes place. A new tuning parameter is unnecessary, since the readily available vigilance parameter can control both attentional tuning and vigilance. The modified fuzzy ART has the self-stabilization property for analog inputs, whether vigilance is fixed or variable
  • Keywords
    ART neural nets; category theory; fuzzy neural nets; search problems; unsupervised learning; attentional tuning mechanism; fuzzy ART; fuzzy adaptive resonance theory neural model; internal competition; multiple categorization; recall; self-stabilization property; vigilance parameter; Adaptive control; Adaptive filters; Business; Fuzzy control; Humans; Information processing; Neural networks; Programmable control; Resonance; Subspace constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks,1997., International Conference on
  • Conference_Location
    Houston, TX
  • Print_ISBN
    0-7803-4122-8
  • Type

    conf

  • DOI
    10.1109/ICNN.1997.614203
  • Filename
    614203