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Globally Exponential Stability of Periodic Solutions to Impulsive Neural Networks with Time‐Varying Delays

Author

Listed:
  • Yuanfu Shao
  • Changjin Xu
  • Qianhong Zhang

Abstract

By using Schaeffer′s theorem and Lyapunov functional, sufficient conditions of the existence and globally exponential stability of positive periodic solution to an impulsive neural network with time‐varying delays are established. Applications, examples, and numerical analysis are given to illustrate the effectiveness of the main results.

Suggested Citation

  • Yuanfu Shao & Changjin Xu & Qianhong Zhang, 2012. "Globally Exponential Stability of Periodic Solutions to Impulsive Neural Networks with Time‐Varying Delays," Abstract and Applied Analysis, John Wiley & Sons, vol. 2012(1).
    • Handle: RePEc:wly:jnlaaa:v:2012:y:2012:i:1:n:358362
    DOI: 10.1155/2012/358362
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    References listed on IDEAS

    as
    1. Chen, Jun & Cui, Baotong, 2008. "Impulsive effects on global asymptotic stability of delay BAM neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 38(4), pages 1115-1125.
    2. Irada A. Dzhalladova & Jaromír Baštinec & Josef Diblík & Denys Y. Khusainov, 2011. "Estimates of Exponential Stability for Solutions of Stochastic Control Systems with Delay," Abstract and Applied Analysis, John Wiley & Sons, vol. 2011(1).
    3. Irada A. Dzhalladova & Jaromír Baštinec & Josef Diblík & Denys Y. Khusainov, 2011. "Estimates of Exponential Stability for Solutions of Stochastic Control Systems with Delay," Abstract and Applied Analysis, Hindawi, vol. 2011, pages 1-14, May.
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    Cited by:

    1. Kuo-Shou Chiu, 2013. "Existence and Global Exponential Stability of Equilibrium for Impulsive Cellular Neural Network Models with Piecewise Alternately Advanced and Retarded Argument," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).

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