• DocumentCode
    1639320
  • Title

    Exponential Stability of Delayed High-order Hopfield-type Neural Networks with Diffusion

  • Author

    Xuyang, Lou ; Baotong, Cui

  • Author_Institution
    Southern Yangtze Univ., Wuxi
  • fYear
    2007
  • Firstpage
    83
  • Lastpage
    86
  • Abstract
    This paper considers a generalized model of high-order Hopfield-type neural networks with time-varying delays and reaction-diffusion terms. By using the method of Lyapunov function and Halanay´s inequality, we investigate the global exponential stability of high-order Hopfield-type neural networks with time-varying delays and reaction-diffusion terms. A sufficient condition for ensuring global exponential stability of these networks is derived, and the estimated exponential convergence rate is also obtained. As an illustration, an numerical example is worked out using the results obtained.
  • Keywords
    Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; reaction-diffusion systems; Lyapunov function; delayed high-order Hopfield-type neural networks; global exponential stability; inequality; reaction-diffusion; time-varying delays; Convergence; Delay effects; Electronic mail; Hopfield neural networks; Lyapunov method; Neural networks; Neurons; Stability; Sufficient conditions; Symmetric matrices; Exponential stability; Lyapunov function; Neural networks; Reaction-diffusion terms; Time-varying delays;
  • 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.2006.4346841
  • Filename
    4346841