• DocumentCode
    281972
  • Title

    VLSI implementation of neural networks

  • Author

    Tarassenko, L. ; Murray, A.F.

  • Author_Institution
    Dept. of Eng. Sci., Oxford Univ., UK
  • fYear
    1989
  • fDate
    32646
  • Firstpage
    42491
  • Lastpage
    42496
  • Abstract
    One of the main contributions to the resurgence of interest in artificial neural networks in the early 80´s was the work of Hopfield (1982) on feedback architectures with nonlinear threshold elements. Since the development of VLSI devices for the implementation of neural networks was initially stimulated by this work, the principles behind the Hopfield model are reviewed briefly. The paper then discusses: general principles of VLSI implementation, analogue VLSI neural networks, and pulse-stream VLSI neural networks
  • Keywords
    VLSI; analogue circuits; neural nets; parallel architectures; Hopfield; VLSI devices; analogue VLSI neural networks; artificial neural networks; feedback architectures; nonlinear threshold elements; pulse-stream VLSI neural networks;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Current Issues in Neural Network Research, IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • Filename
    198478