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Dynamical Behaviors of Stochastic Reaction‐Diffusion Cohen‐Grossberg Neural Networks with Delays

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  • Li Wan
  • Qinghua Zhou
  • Jizi Li

Abstract

This paper investigates dynamical behaviors of stochastic Cohen‐Grossberg neural network with delays and reaction diffusion. By employing Lyapunov method, Poincaré inequality and matrix technique, some sufficient criteria on ultimate boundedness, weak attractor, and asymptotic stability are obtained. Finally, a numerical example is given to illustrate the correctness and effectiveness of our theoretical results.

Suggested Citation

  • Li Wan & Qinghua Zhou & Jizi Li, 2012. "Dynamical Behaviors of Stochastic Reaction‐Diffusion Cohen‐Grossberg Neural Networks with Delays," Abstract and Applied Analysis, John Wiley & Sons, vol. 2012(1).
    • Handle: RePEc:wly:jnlaaa:v:2012:y:2012:i:1:n:369725
    DOI: 10.1155/2012/369725
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    References listed on IDEAS

    as
    1. Song, Qiankun & Zhao, Zhenjiang, 2005. "Global dissipativity of neural networks with both variable and unbounded delays," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 393-401.
    2. Lou, Xu Yang & Cui, Bao Tong, 2008. "Global robust dissipativity for integro-differential systems modeling neural networks with delays," Chaos, Solitons & Fractals, Elsevier, vol. 36(2), pages 469-478.
    3. Zhao, Hongyong & Ding, Nan & Chen, Ling, 2009. "Almost sure exponential stability of stochastic fuzzy cellular neural networks with delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1653-1659.
    4. Chen, Zhang & Ruan, Jiong, 2007. "Global dynamic analysis of general Cohen–Grossberg neural networks with impulse," Chaos, Solitons & Fractals, Elsevier, vol. 32(5), pages 1830-1837.
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