• DocumentCode
    1682898
  • Title

    Dynamic neural networks for nonlinear systems identification

  • Author

    Sanchez, Edgar N.

  • Author_Institution
    FIME, Univ. Autonoma de Nuevo Leon, San Nicolas de los Garza, Mexico
  • Volume
    3
  • fYear
    1994
  • Firstpage
    2480
  • Abstract
    This paper approaches nonlinear system identification as operator approximation. A neural network, which can identify nonlinear systems, is presented. The identification is performed by the arbitrarily well approximation of time-invariant causal and continuous operators, which have fading memory. A theorem about this property is stated and proved
  • Keywords
    approximation theory; identification; neural nets; nonlinear systems; continuous operator; dynamic neural networks; fading memory; identification; nonlinear systems; operator approximation; time-invariant causal operator; Biological system modeling; Fading; Hopfield neural networks; Neural networks; Neurons; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; System identification; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
  • Conference_Location
    Lake Buena Vista, FL
  • Print_ISBN
    0-7803-1968-0
  • Type

    conf

  • DOI
    10.1109/CDC.1994.411513
  • Filename
    411513
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1682898