• DocumentCode
    914816
  • Title

    Cellular neural networks for associative memories

  • Author

    Liu, Derong ; Michel, Anthony N.

  • Author_Institution
    Dept. of Electr. Eng., Notre Dame Univ., IN, USA
  • Volume
    40
  • Issue
    2
  • fYear
    1993
  • fDate
    2/1/1993 12:00:00 AM
  • Firstpage
    119
  • Lastpage
    121
  • Abstract
    A synthesis procedure for designing nonsymmetric cellular neural networks (CNN) with a predetermined local interconnection structure that will store a set of desired bipolar vectors as memory points is presented. A specific case of constructing Chinese characters is presented to demonstrate the applicability of the results. Simulation results show that all the vectors corresponding to 50 commonly used Chinese characters are reachable memory vectors of the synthesized CNN
  • Keywords
    cellular arrays; character recognition; character sets; content-addressable storage; neural nets; Chinese characters; associative memories; bipolar vectors storage; character construction; local interconnection structure; nonsymmetric cellular neural networks; synthesis procedure; Associative memory; Cellular neural networks; Circuit synthesis; Eigenvalues and eigenfunctions; Equations; Image processing; Network synthesis; Neural networks; Signal synthesis; 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
    10.1109/82.219843
  • Filename
    219843