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Asymptotic Stability and Exponential Stability of Impulsive Delayed Hopfield Neural Networks

Author

Listed:
  • Jing Chen
  • Xiaodi Li
  • Dequan Wang

Abstract

A criterion for the uniform asymptotic stability of the equilibrium point of impulsive delayed Hopfield neural networks is presented by using Lyapunov functions and linear matrix inequality approach. The criterion is a less restrictive version of a recent result. By means of constructing the extended impulsive Halanay inequality, we also analyze the exponential stability of impulsive delayed Hopfield neural networks. Some new sufficient conditions ensuring exponential stability of the equilibrium point of impulsive delayed Hopfield neural networks are obtained. An example showing the effectiveness of the present criterion is given.

Suggested Citation

  • Jing Chen & Xiaodi Li & Dequan Wang, 2013. "Asymptotic Stability and Exponential Stability of Impulsive Delayed Hopfield Neural Networks," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:638496
    DOI: 10.1155/2013/638496
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    References listed on IDEAS

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    1. Xia, Yonghui & Wong, Patricia J.Y., 2009. "Global exponential stability of a class of retarded impulsive differential equations with applications," Chaos, Solitons & Fractals, Elsevier, vol. 39(1), pages 440-453.
    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.
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    4. 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.
    5. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2005. "New stability conditions for neural networks with constant and variable delays," Chaos, Solitons & Fractals, Elsevier, vol. 26(5), pages 1391-1398.
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