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Global Robust Passivity Analysis for Stochastic Interval Neural Networks with Interval Time-Varying Delays and Markovian Jumping Parameters

Author

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  • P. Balasubramaniam

    (Gandhigram Rural Institute-Deemed University)

  • G. Nagamani

    (Gandhigram Rural Institute-Deemed University)

Abstract

In this paper, the problem of passivity analysis is investigated for stochastic interval neural networks with interval time-varying delays and Markovian jumping parameters. By constructing a proper Lyapunov-Krasovskii functional, utilizing the free-weighting matrix method and some stochastic analysis techniques, we deduce new delay-dependent sufficient conditions, that ensure the passivity of the proposed model. These sufficient conditions are computationally efficient and they can be solved numerically by linear matrix inequality (LMI) Toolbox in Matlab. Finally, numerical examples are given to verify the effectiveness and the applicability of the proposed results.

Suggested Citation

  • P. Balasubramaniam & G. Nagamani, 2011. "Global Robust Passivity Analysis for Stochastic Interval Neural Networks with Interval Time-Varying Delays and Markovian Jumping Parameters," Journal of Optimization Theory and Applications, Springer, vol. 149(1), pages 197-215, April.
    • Handle: RePEc:spr:joptap:v:149:y:2011:i:1:d:10.1007_s10957-010-9770-6
    DOI: 10.1007/s10957-010-9770-6
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    References listed on IDEAS

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    Cited by:

    1. Samidurai, Rajendran & Manivannan, Raman, 2015. "Robust passivity analysis for stochastic impulsive neural networks with leakage and additive time-varying delay components," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 743-762.

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