Robust stability for uncertain delayed fuzzy Hopfield neural networks with Markovian jumping parameters

Hongyi Li, B. Chen, Z. Qi, Q. Weiyi

    Research output: Contribution to journalArticlepeer-review

    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.
    Original languageEnglish
    Pages (from-to)94-102
    Number of pages9
    JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
    Volume39
    Issue number1
    DOIs
    Publication statusPublished - Feb 2009

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