• DocumentCode
    1564003
  • Title

    Stability Analysis of Continuous Hopfield Neural Networks with Delay

  • Author

    Cong, Jin ; Wang, Shihui

  • Author_Institution
    Dept. of Comput. Sci., Central China Normal Univ., Wuhan
  • Volume
    1
  • fYear
    2005
  • Firstpage
    573
  • Lastpage
    575
  • Abstract
    In this paper, by constructing a new Lyapunov functional, problem of the global asymptotic stability is discussed for the continuous Hopfield neural networks with delays. A simple and new sufficient condition is obtained ensuring existence, uniqueness of the equilibrium point and its global asymptotic stability of the neural networks. This condition can be used to design globally asymptotic stable networks and thus have important significance in both theory and applications
  • Keywords
    Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; Lyapunov functional; continuous Hopfield neural networks; delays; global asymptotic stability; stability analysis; Asymptotic stability; Computer science; Delay effects; Differential equations; Electronic mail; Hopfield neural networks; Neural networks; Recurrent neural networks; Stability analysis; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9422-4
  • Type

    conf

  • DOI
    10.1109/ICNNB.2005.1614678
  • Filename
    1614678