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Improved delay-dependent stability analysis for uncertain stochastic neural networks with time-varying delay

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Abstract

This paper focuses on the problem of delay-dependent robust stability analysis for a class of uncertain stochastic neural networks with time-varying delay by employing improved free-weighting matrix method. Taking the relationship among the time-varying delay, its upper bound and their difference into account and using \(\hbox{It}\hat{o}\hbox{'s}\) differential formula, some improved LMI-based delay-dependent stability criteria for stochastic neural networks are obtained without ignoring any terms, which guarantee systems globally robustly stochastically stable in the mean square. Finally, three numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (No.60425310) and (No.60974026) and in part by the Doctor Subject Foundation of China (No.200805330004) and in part by the Program for New Century Excellent Talents in University (No. NCET-06-0679) and in part by the Hunan Provincial National Natural Science Foundation of China (No. 08JJ1010) and in part by the Hunan Provincial Innovation Foundation For Postgraduate.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, 410083, Changsha, China

    Fang Liu, Min Wu & Yong He

  2. Graduate School of Environmental and Energy Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo, 169-8555, Japan

    Fang Liu & Ryuichi Yokoyama

Authors
  1. Fang Liu
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  2. Min Wu
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  3. Yong He
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  4. Ryuichi Yokoyama
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Correspondence to Min Wu.

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Liu, F., Wu, M., He, Y. et al. Improved delay-dependent stability analysis for uncertain stochastic neural networks with time-varying delay. Neural Comput & Applic 20, 441–449 (2011). https://doi.org/10.1007/s00521-010-0408-2

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  • DOI: https://doi.org/10.1007/s00521-010-0408-2

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