• DocumentCode
    2662038
  • Title

    VLSI implementation of cellular neural networks

  • Author

    Yang, L. ; Chua, L.O. ; Krieg, K.R.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
  • fYear
    1990
  • fDate
    1-3 May 1990
  • Firstpage
    2425
  • Abstract
    A cellular neural network (CNN) which is an example of very-large-scale analog processing or collective analog computation is presented. The CNN architecture combines some features of fully connected analog neural networks with the nearest-neighbor interactions found in cellular automata. VLSI implementation of these circuits is discussed. Though the circuits described have been fabricated for noise removal and connected segment extraction, most of the features of the VLSI circuits are shared by VLSI implementations of other processing functions
  • Keywords
    VLSI; analogue computer circuits; computer architecture; neural nets; pattern recognition; VLSI implementation; cellular neural networks; collective analog computation; connected segment extraction; fully connected analog neural networks; nearest-neighbor interactions; noise removal; very-large-scale analog processing; Analog computers; Cellular neural networks; Circuit noise; Computer architecture; Fabrication; Feedback circuits; Force feedback; Large-scale systems; Neural networks; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1990., IEEE International Symposium on
  • Conference_Location
    New Orleans, LA
  • Type

    conf

  • DOI
    10.1109/ISCAS.1990.112500
  • Filename
    112500