• DocumentCode
    1015143
  • Title

    Robust Stability for Uncertain Delayed Fuzzy Hopfield Neural Networks With Markovian Jumping Parameters

  • Author

    Li, Hongyi ; Chen, Bing ; Zhou, Qi ; Qian, Weiyi

  • Author_Institution
    Inst. of Complexity Sci., Qingdao Univ., Qingdao
  • Volume
    39
  • Issue
    1
  • fYear
    2009
  • Firstpage
    94
  • Lastpage
    102
  • Abstract
    This paper is concerned with the problem of the robust stability of nonlinear delayed Hopfield neural networks (HNNs) with Markovian jumping parameters by Takagi-Sugeno (T-S) fuzzy model. The nonlinear delayed HNNs are first established as a modified T-S fuzzy model in which the consequent parts are composed of a set of Markovian jumping HNNs with interval delays. Time delays here are assumed to be time-varying and belong to the given intervals. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality approach, stability conditions are proposed in terms of the upper and lower bounds of the delays. Finally, numerical examples are used to illustrate the effectiveness of the proposed method.
  • Keywords
    Hopfield neural nets; Lyapunov methods; Markov processes; delay systems; fuzzy control; fuzzy set theory; linear matrix inequalities; neurocontrollers; robust control; uncertain systems; Lyapunov-Krasovskii stability theory; Markovian jumping parameters; T-S fuzzy model; Takagi-Sugeno fuzzy model; linear matrix inequality approach; robust stability; uncertain delayed fuzzy Hopfield neural networks; Fuzzy systems; Hopfield neural networks (HNNs); interval delays; linear matrix inequalities (LMIs); stochastic stability; Algorithms; Fuzzy Logic; Markov Chains; Neural Networks (Computer); Nonlinear Dynamics; Time Factors;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4419
  • Type

    jour

  • DOI
    10.1109/TSMCB.2008.2002812
  • Filename
    4694079