ON DESIGNING FUZZY LEARNING NEURAL-AUTOMATA.

L. C. Shiue, R. O. Grondin

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Scopus citations

    Abstract

    A structured approach to the design of neural-like learning automata. A novel fuzzy neuron is used as a basic processing element in building such automata. The possibility of implementing neural networks by VLSI circuits is explored. It is shown that a parallel automaton can be realized directly from specified fuzzy production rules. By reinforcing the fuzzy grades of membership of production rules, a fuzzy learning machine is obtained. This approach can also be applied to the construction of stochastic neural automata by using multiply-add operations instead of max-min rules.

    Original languageEnglish (US)
    Title of host publicationUnknown Host Publication Title
    EditorsMaureen Caudill, Charles T. Butler, San Diego Adaptics
    Place of PublicationSan Diego, CA, USA
    PublisherSOS Printing
    StatePublished - 1987

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    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Shiue, L. C., & Grondin, R. O. (1987). ON DESIGNING FUZZY LEARNING NEURAL-AUTOMATA. In M. Caudill, C. T. Butler, & S. D. Adaptics (Eds.), Unknown Host Publication Title SOS Printing.