• DocumentCode
    294352
  • Title

    Stability criteria of discrete-time analog neural networks

  • Author

    Jin, Liang ; Gupta, Madan M. ; Nikiforuk, Peter N.

  • Author_Institution
    Intelligent Syst. Res. Lab., Saskatchewan Univ., Saskatoon, Sask., Canada
  • Volume
    3
  • fYear
    1995
  • fDate
    13-15 Dec 1995
  • Firstpage
    3040
  • Abstract
    In this short paper, some globally asymptotical stability criteria for the equilibrium states of a class of discrete-time dynamic neural networks with continuous states and asymmetrical weight matrices are presented. The resulting stability criteria are represented by either the existence of the positive diagonal solutions of the Lyapunov equations or some inequalities. Finally, some examples are provided for demonstrating the global stability conditions presented
  • Keywords
    asymptotic stability; discrete time systems; neural nets; stability criteria; Lyapunov equations; asymmetrical weight matrices; continuous states; discrete-time analog neural networks; equilibrium states; global stability; globally asymptotical stability criteria; Educational institutions; Equations; Intelligent networks; Intelligent systems; Laboratories; Linear matrix inequalities; Lyapunov method; Neural networks; Stability criteria; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
  • Conference_Location
    New Orleans, LA
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-2685-7
  • Type

    conf

  • DOI
    10.1109/CDC.1995.478609
  • Filename
    478609
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=294352