• DocumentCode
    2831034
  • Title

    VLSI implementation of a pulse Hebbian learning law

  • Author

    Meador, Jack ; Watola, David ; Nintunze, Novat

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USA
  • fYear
    1991
  • fDate
    11-14 Jun 1991
  • Firstpage
    1287
  • Abstract
    The authors describe a Hebbian learning rule which is particularly well suited for VLSI implementation. The authors first introduce a signal coding method where signal information is represented as pulse probabilities. The authors then briefly describe the functionality of an impulse neuron circuit in terms of that method. Competitive learning is then reviewed in the context of the probabilistic representation. The pulse Hebbian learning law is then introduced and analyzed in these terms. The authors close with an example of a simple pulse Hebbian synapse circuit for use in a competitive neural network
  • Keywords
    VLSI; encoding; learning systems; neural nets; signal processing; VLSI implementation; competitive neural network; impulse neuron circuit; pulse Hebbian learning law; pulse Hebbian synapse circuit; pulse probabilities; signal coding method; Backpropagation algorithms; Hebbian theory; Neural networks; Neurons; Probability; Pulse circuits; Pulse width modulation; Signal representations; Space vector pulse width modulation; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1991., IEEE International Sympoisum on
  • Print_ISBN
    0-7803-0050-5
  • Type

    conf

  • DOI
    10.1109/ISCAS.1991.176605
  • Filename
    176605