• DocumentCode
    1643550
  • Title

    Cellular neural network design with continuous signals

  • Author

    Schwarz, Stephan ; Mathis, Wolfgang

  • Author_Institution
    Dept. of Electr. Eng., Wuppertal Univ., Germany
  • fYear
    1992
  • Firstpage
    17
  • Lastpage
    22
  • Abstract
    Basic design methods for the class of cellular neural networks (CNNs) with continuous input signals are introduced. The realistic model of CNNs proposed by L.O. Chua and L. Yang (1988) combines components of the Hopfield-net, cellular automata, and of cellular systems. The CNN design methods integrate special conditions for technical architectures with respect to real-time implementations. Hacijan´s polynomial solution method is applied to solve the set of linear inequalities which correspond with the CNN design
  • Keywords
    image processing; linear programming; neural nets; polynomials; CNN; Hopfield-net; cellular automata; cellular neural networks; continuous signals; design; linear inequalities; polynomial; Cellular neural networks; Circuit synthesis; Cloning; Computer networks; Delay; Design methodology; Nonlinear equations; Output feedback; Polynomials; Signal design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and their Applications, 1992. CNNA-92 Proceedings., Second International Workshop on
  • Conference_Location
    Munich
  • Print_ISBN
    0-7803-0875-1
  • Type

    conf

  • DOI
    10.1109/CNNA.1992.274333
  • Filename
    274333