• DocumentCode
    2515988
  • Title

    Evaluation of CNN template robustness towards VLSI implementation

  • Author

    Kinget, Peter ; Steyaert, Michiel

  • Author_Institution
    Dept. Electrotech., Katholieke Univ., Leuven, Belgium
  • fYear
    1994
  • fDate
    18-21 Dec 1994
  • Firstpage
    381
  • Lastpage
    386
  • Abstract
    In this paper a method for the evaluation of the static robustness of cellular neural network (CNN) templates is proposed. From this evaluation the circuit accuracy specifications for a VLSI implementation can be derived which allows the designer to optimize the performance. Moreover, from this evaluation method guidelines for robust template designs can be derived and parameter testing templates can be developed
  • Keywords
    VLSI; cellular neural nets; VLSI implementation; cellular neural network; circuit accuracy specifications; parameter testing; static robustness; template robustness; Cellular neural networks; Circuit testing; Design optimization; Digital circuits; Electronic mail; Gaussian distribution; Guidelines; Hardware; Robustness; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on
  • Conference_Location
    Rome
  • Print_ISBN
    0-7803-2070-0
  • Type

    conf

  • DOI
    10.1109/CNNA.1994.381645
  • Filename
    381645