• DocumentCode
    3197543
  • Title

    Neuro-fuzzy logic

  • Author

    Glorennec, Pierre-Yves

  • Author_Institution
    Inst. Nat. des Sci. Appliques, Rennes, France
  • Volume
    2
  • fYear
    1996
  • fDate
    8-11 Sep 1996
  • Firstpage
    899
  • Abstract
    Neural VLSI devices are now available and it would be interesting to use them for logical operations. We show that, in the Lukasiewicz logic, it is possible to use an artificial neuron to implement four basic logical operators (conjunction, disjunction, implication and negation). A new operator, AND-OR, is introduced with the same formalism. Finally, a smoothed form of the logical operators make it possible for their implementation on actual hardware
  • Keywords
    fuzzy logic; fuzzy neural nets; generalisation (artificial intelligence); inference mechanisms; learning (artificial intelligence); neural nets; uncertainty handling; AND-OR operator; Lukasiewicz logic; artificial neuron; conjunction; disjunction; fuzzy inference; generalisation; neuro-fuzzy logic; Boolean functions; Fuzzy logic; Hardware; Logic devices; Neurons; Open wireless architecture; Smoothing methods; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-7803-3645-3
  • Type

    conf

  • DOI
    10.1109/FUZZY.1996.552298
  • Filename
    552298