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Stochastic Dynamics of Nonautonomous Cohen‐Grossberg Neural Networks

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  • Chuangxia Huang
  • Jinde Cao

Abstract

This paper is devoted to the study of the stochastic stability of a class of Cohen‐Grossberg neural networks, in which the interconnections and delays are time‐varying. With the help of Lyapunov function, Burkholder‐Davids‐Gundy inequality, and Borel‐Cantell′s theory, a set of novel sufficient conditions on pth moment exponential stability and almost sure exponential stability for the trivial solution of the system is derived. Compared with the previous published results, our method does not resort to the Razumikhin‐type theorem and the semimartingale convergence theorem. Results of the development as presented in this paper are more general than those reported in some previously published papers. An illustrative example is also given to show the effectiveness of the obtained results.

Suggested Citation

  • Chuangxia Huang & Jinde Cao, 2011. "Stochastic Dynamics of Nonautonomous Cohen‐Grossberg Neural Networks," Abstract and Applied Analysis, John Wiley & Sons, vol. 2011(1).
    • Handle: RePEc:wly:jnlaaa:v:2011:y:2011:i:1:n:297147
    DOI: 10.1155/2011/297147
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    References listed on IDEAS

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    1. Park, Ju H., 2009. "Synchronization of cellular neural networks of neutral type via dynamic feedback controller," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1299-1304.
    2. Zhu, Wenli & Hu, Jin, 2006. "Stability analysis of stochastic delayed cellular neural networks by LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 29(1), pages 171-174.
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