• DocumentCode
    1343706
  • Title

    An asynchronous weightless neural network for discrete relaxation problems

  • Author

    Alnuweiri, H.M. ; Gange, D.

  • Author_Institution
    Centre for Integrated Comput. Res., British Columbia Univ., Vancouver, BC, Canada
  • Volume
    45
  • Issue
    2
  • fYear
    1998
  • fDate
    2/1/1998 12:00:00 AM
  • Firstpage
    210
  • Lastpage
    216
  • Abstract
    This paper proposes a weightless neural network for solving discrete relaxation problems. The network implements a parallel version of a new efficient sequential algorithm for the consistent labeling problem. The proposed neural network consists of a feedback interconnection of three layers of very simple neurons that operate in an asynchronous fashion. Because of the simple structure of the neurons, the neural network can be implemented using highly regular AND/OR VLSI arrays. The asynchronous operation eliminates the need for using clocks or placing registers between the different layers and along the feedback paths of the network, thus resulting in very fast convergence time
  • Keywords
    CMOS digital integrated circuits; VLSI; asynchronous circuits; circuit feedback; convergence of numerical methods; neural chips; neural net architecture; parallel algorithms; parallel architectures; relaxation theory; asynchronous weightless neural network; consistent labeling problem; fast convergence time; feedback interconnection; highly regular AND/OR VLSI arrays; iscrete relaxation problems; Clocks; Convergence; Integrated circuit interconnections; Labeling; Logic gates; Neural networks; Neurofeedback; Neurons; Registers; Very large scale integration;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7130
  • Type

    jour

  • DOI
    10.1109/82.661652
  • Filename
    661652