• DocumentCode
    2434536
  • Title

    Object oriented VLSI design automation for pulse coded neural networks

  • Author

    Hylander, Paul ; Meador, Jack

  • Author_Institution
    Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USA
  • Volume
    3
  • fYear
    1994
  • fDate
    27 Jun-2 Jul 1994
  • Firstpage
    1825
  • Abstract
    Pulse coded neural networks employ special purpose mixed signal circuits which emulate to varying degrees the temporal behavior of natural neurons. It has long been difficult to verify pulse coded neural network implementations of significant complexity prior to fabrication using conventional design automation tools. In this paper, we introduce SPINACH, an objected oriented solution to the problems of pulse-coded neural network hardware simulation and synthesis. SPINACH is a C++ object library intended for the specification and simulation of pulse-coded neural network hardware. As such, it fulfils the purpose of a specialized mixed-signal hardware description language (HDL) complete with both large-scale simulation capabilities and also circuit synthesis when combined with a commercial VLSI design system
  • Keywords
    VLSI; circuit CAD; digital simulation; hardware description languages; integrated circuit design; neural chips; object-oriented methods; C++ object library; SPINACH; VLSI design automation; circuit CAD; circuit synthesis; large-scale simulation; mixed-signal hardware description language; objected oriented method; pulse coded neural networks; Circuit simulation; Circuit synthesis; Design automation; Hardware design languages; Neural network hardware; Neural networks; Neurons; Object oriented modeling; Pulse circuits; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1901-X
  • Type

    conf

  • DOI
    10.1109/ICNN.1994.374435
  • Filename
    374435