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Synchronization of Chaotic Delayed Fuzzy Neural Networks under Impulsive and Stochastic Perturbations

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  • Bing Li
  • Qiankun Song

Abstract

The synchronization problem of chaotic fuzzy cellular neural networks with mixed delays is investigated. By an impulsive integrodifferential inequality and the Itô′s formula, some sufficient criteria to synchronize the networks under both impulsive and stochastic perturbations are obtained. The example and simulations are given to demonstrate the efficiency and advantages of the proposed results.

Suggested Citation

  • Bing Li & Qiankun Song, 2013. "Synchronization of Chaotic Delayed Fuzzy Neural Networks under Impulsive and Stochastic Perturbations," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:543549
    DOI: 10.1155/2013/543549
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    References listed on IDEAS

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    1. Huang, Tingwen, 2007. "Exponential stability of delayed fuzzy cellular neural networks with diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 31(3), pages 658-664.
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    3. Yang, Xinsong & Huang, Chuangxia & Zhu, Quanxin, 2011. "Synchronization of switched neural networks with mixed delays via impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 44(10), pages 817-826.
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    5. Cao, Jinde & Wang, Zidong & Sun, Yonghui, 2007. "Synchronization in an array of linearly stochastically coupled networks with time delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 718-728.
    6. 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.
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    Cited by:

    1. Chen, Guangxun & Wang, Yantao & Zhang, Xian, 2025. "New global exponential synchronization conditions for impulsive chaotic neural networks with multiple time-varying leakage and transmission delays: Applications for secure communications," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).

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