A mathematical model for an adaptive fuzzy neuron is proposed. Each neuron within a network corresponds to a fuzzy inference rule. These neurons may learn from experience via the adaptation of synaptic modifiers. The parallel structure of a fuzzy neural network controller enables complex decisions to be made in real-time. A simplified example of a neural network for controlling the steering of an automobile is used to illustrate these notions.


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    Title :

    Fuzzy neural network approach to control systems


    Additional title:

    Ein neuronaler Netzansatz auf Fuzzy-Basis für Regelungssysteme


    Contributors:
    Gupta, M.M. (author) / Knopf, G.K. (author)


    Publication date :

    1991


    Size :

    6 Seiten, 7 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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