• DocumentCode
    3181290
  • Title

    Stability analysis of recurrent neural networks - a Volterra integro-differential equation approach

  • Author

    Liu, Pingzhou ; Han, Qing-Long

  • Author_Institution
    Fac. of Informatics & Commun., Central Queensland Univ., Rockhampton, Qld., Australia
  • Volume
    5
  • fYear
    2004
  • fDate
    2004
  • Firstpage
    5415
  • Abstract
    The stability of a special class of nonlinear Volterra integro-differential systems are analyzed by comparing them to linear Volterra integro-differential systems. The results are used to determine the stability properties of recurrent neural networks with distributed delays, including constant discrete delays as a special case. The obtained stability criteria have unified and extended many existing results on recurrent neural networks.
  • Keywords
    Volterra equations; asymptotic stability; delays; integro-differential equations; nonlinear equations; recurrent neural nets; Volterra integro-differential equation approach; constant discrete delays; distributed delays; nonlinear Volterra integro-differential systems; recurrent neural networks; stability analysis; stability criteria; Biological neural networks; Delay effects; Integrodifferential equations; Neural networks; Neurodynamics; Neurons; Recurrent neural networks; Stability analysis; Stability criteria; Symmetric matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2004. CDC. 43rd IEEE Conference on
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-8682-5
  • Type

    conf

  • DOI
    10.1109/CDC.2004.1429669
  • Filename
    1429669