• DocumentCode
    304038
  • Title

    Implementing fuzzy logic control with a biologically plausible neural net

  • Author

    Alexander, John R., Jr.

  • Author_Institution
    Towson State Univ., MD, USA
  • Volume
    2
  • fYear
    1996
  • fDate
    8-11 Sep 1996
  • Firstpage
    886
  • Abstract
    Abeles (1982) and Alkon et al. (1989) stressed the fact that neurons possess an average firing rate, and may fire both above or below this average. The equations developed by the author (1991) (called the RX equations) include an average firing rate. The RX equations have been shown to be useful in solving elementary control problems. In fact, control, on a par with a fuzzy logic controller, may be achieved by a network of as few as three neurons, two input and one output-a three-neuron controller (TNC). In this paper we discuss the analogies between fuzzy logic control and control exercised by a TNC and the restrictions existing in application of the TNC technique
  • Keywords
    fuzzy control; neurocontrollers; RX equations; average firing rate; biologically plausible neural net; fuzzy logic control; three-neuron controller; Biological control systems; Control systems; Differential equations; Fuzzy logic; Input variables; Mathematics; Neural networks; Neurons; Nonlinear equations;
  • 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.1996.552296
  • Filename
    552296