• DocumentCode
    1640567
  • Title

    Impulsive Synchronization of Typical Hopfield Neural Networks

  • Author

    Qunli, Zhang ; Guanjun, Jia

  • Author_Institution
    Heze Univ., Heze
  • fYear
    2007
  • Firstpage
    270
  • Lastpage
    273
  • Abstract
    This paper is mainly concerned with the issues of impulsive control for synchronization of Hopfield neural networks. By using stability theory of impulsive dynamical systems, some simple yet generic criteria are derived ensuring the robust synchronization of Hopfield neural networks. Moreover, the approaches developed here further extend the techniques presented in recent literature. To this end, the theoretical results are applied to a typical delayed chaotic Hopfield neural networks and an autonomous chaotic Hopfield neural networks, and numerical simulations also demonstrate the effectiveness and feasibility of the proposed technique.
  • Keywords
    Hopfield neural nets; Lyapunov methods; differential equations; stability; synchronisation; Lyapunov stability; chaotic Hopfield neural networks; differential equations; impulsive control; impulsive dynamical systems; impulsive synchronization; Cellular neural networks; Chaos; Control systems; Differential equations; Hopfield neural networks; Master-slave; Neural networks; Numerical simulation; Recurrent neural networks; Robust stability; Chaos synchronization; Gronwall Inequality; Hopfield neural networks; Impulsive control; Lyapunov stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2007. CCC 2007. Chinese
  • Conference_Location
    Hunan
  • Print_ISBN
    978-7-81124-055-9
  • Electronic_ISBN
    978-7-900719-22-5
  • Type

    conf

  • DOI
    10.1109/CHICC.2006.4346890
  • Filename
    4346890