• DocumentCode
    1686088
  • Title

    Improved delay-dependent stability criterion on neural networks with time-varying delay

  • Author

    Zhang, Haitao ; Wang, Ting ; Fei, Shumin ; Li, Tao

  • Author_Institution
    Key Lab. of Meas. & Control of CSE, Southeast Univ., Nanjing, China
  • fYear
    2010
  • Firstpage
    2080
  • Lastpage
    2084
  • Abstract
    In this paper, based on Lyapunov-Krasovskii functional approach and proper integral inequality, one novel sufficient condition is derived to guarantee the global stability for neural networks with interval time-varying delay, in which the general convex combination is employed. The LMI-based criterion heavily depends on the upper and lower bounds on both time delay and its derivative, which is different from those existent ones and has wider application fields than some present results. Finally, two numerical examples can illustrate the less conservatism of the proposed methods.
  • Keywords
    asymptotic stability; convex programming; delays; linear matrix inequalities; neural nets; stability criteria; time-varying systems; LMI; Lyapunov Krasovskii function; convex combination; delay dependent stability criteria; integral inequality; neural network; time varying delay; Artificial neural networks; Asymptotic stability; Delay; Delay effects; Numerical stability; Stability criteria; Delayed neural networks (DNNs); LMI technique; Lyapunov-Krasovskii functional (LKF); asymptotical stability; time-varying delay;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2010 8th World Congress on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-6712-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2010.5554390
  • Filename
    5554390