• DocumentCode
    341397
  • Title

    Unifying results in CNN theory using delta operator

  • Author

    Hänggi, Martin ; Reddy, H. ; Moschytz, G.

  • Volume
    5
  • fYear
    1999
  • fDate
    May 30 1999-June 2 1999
  • Firstpage
    547
  • Abstract
    By means of the delta operator, a new type of CNN, the (/spl delta/,c)-CNN, is introduced. It is a superclass of continuous-time (CT) and discrete-time (DT) CNNs with any saturation-, high-gain-, or hardlimiting sign-nonlinearity. It is shown that the (/spl delta/,c)-CNN allows continuous transition between different types of nonlinearities and between CT- and DT-CNNs, providing a unifying framework for CNN theory. In particular, the problem of optimally robust template design can be dealt with in a unified manner.
  • Keywords
    cellular neural nets; continuous time systems; discrete time systems; (/spl delta/,c)-CNN; CNN theory; continuous-time CNN; delta operator; discrete-time CNN; hardlimiting sign-nonlinearity; high-gain-nonlinearity; optimally robust template design; saturation-nonlinearity; Boundary conditions; Cellular neural networks; Convolution; Information processing; Inspection; Laboratories; Nonlinear equations; Robustness; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1999. ISCAS '99. Proceedings of the 1999 IEEE International Symposium on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-5471-0
  • Type

    conf

  • DOI
    10.1109/ISCAS.1999.777630
  • Filename
    777630