• DocumentCode
    3284244
  • Title

    Stability of switched Hopfield neural networks with time-varying delay

  • Author

    Kai Zhang ; Jie Lian ; Xi-Ming Sun ; Dong Wang

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol., Dalian, China
  • fYear
    2010
  • fDate
    June 30 2010-July 2 2010
  • Firstpage
    4943
  • Lastpage
    4948
  • Abstract
    This paper considers the asymptotic stability problem for switched Hopfield neural networks with time-varying delay under hysteretic switching rule. The parameter uncertainties are considered and assumed to be norm bounded. Single Lyapunov function method is used to analyze the stability property and design the hysteretic switching rule, which is designed according to current state and the previous value of switched signal. Sufficient conditions are given in terms of linear matrix inequalities (LMIs) to guarantee the stability of the system. An example illustrates the effectiveness of the proposed theory.
  • Keywords
    Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; time-varying systems; uncertain systems; asymptotic stability problem; hysteretic switching rule; linear matrix inequality; parameter uncertainty; single Lyapunov function method; switched Hopfield neural network; time varying delay; Asymptotic stability; Hopfield neural networks; Hysteresis; Linear matrix inequalities; Lyapunov method; Signal analysis; Signal design; Stability analysis; Sufficient conditions; Uncertain systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2010
  • Conference_Location
    Baltimore, MD
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-7426-4
  • Type

    conf

  • DOI
    10.1109/ACC.2010.5530932
  • Filename
    5530932