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Global μ‐Stability Analysis for Impulsive Stochastic Neural Networks with Unbounded Mixed Delays

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  • Lizi Yin
  • Xinchun Wang

Abstract

We investigate the global μ‐stability in the mean square of impulsive stochastic neural networks with unbounded time‐varying delays and continuous distributed delays. By choosing an appropriate Lyapunov‐Krasovskii functional, a novel robust stability condition, in the form of linear matrix inequalities, is derived. These sufficient conditions can be tested by MATLAB LMI software packages. The results extend and improve the earlier publication. Two numerical examples are provided to illustrate the effectiveness of the obtained theoretical results.

Suggested Citation

  • Lizi Yin & Xinchun Wang, 2013. "Global μ‐Stability Analysis for Impulsive Stochastic Neural Networks with Unbounded Mixed Delays," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:746241
    DOI: 10.1155/2013/746241
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    References listed on IDEAS

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    1. Zhou, Jin & Xiang, Lan & Liu, Zengrong, 2007. "Synchronization in complex delayed dynamical networks with impulsive effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 684-692.
    2. Zhang, Qiang & Xu, Xiaopeng Wei Jin, 2007. "Delay-dependent global stability results for delayed Hopfield neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 662-668.
    3. Li, Ping & Cao, Jinde & Wang, Zidong, 2007. "Robust impulsive synchronization of coupled delayed neural networks with uncertainties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 261-272.
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