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Global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms

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  • Wang, Xiaohu
  • Xu, Daoyi

Abstract

In this paper, the global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms is considered. By establishing an integro-differential inequality with impulsive initial condition and using the properties of M-cone and eigenspace of the spectral radius of nonnegative matrices, several new sufficient conditions are obtained to ensure the global exponential stability of the equilibrium point for fuzzy cellular neural networks with delays and reaction-diffusion terms. These results extend and improve the earlier publications. Two examples are given to illustrate the efficiency of the obtained results.

Suggested Citation

  • Wang, Xiaohu & Xu, Daoyi, 2009. "Global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 2713-2721.
    • Handle: RePEc:eee:chsofr:v:42:y:2009:i:5:p:2713-2721
    DOI: 10.1016/j.chaos.2009.03.177
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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.
    2. Xia, Yonghui & Cao, Jinde & Huang, Zhenkun, 2007. "Existence and exponential stability of almost periodic solution for shunting inhibitory cellular neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 34(5), pages 1599-1607.
    3. Zhu, Wei & Xu, Daoyi & Huang, Yumei, 2008. "Global impulsive exponential synchronization of time-delayed coupled chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 35(5), pages 904-912.
    4. Liu, Bingwen & Huang, Lihong, 2007. "Existence and stability of almost periodic solutions for shunting inhibitory cellular neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 31(1), pages 211-217.
    5. Xiong, Wanmin & Zhou, Qiyuan & Xiao, Bing & Yu, Yuehua, 2007. "Global exponential stability of cellular neural networks with mixed delays and impulses," Chaos, Solitons & Fractals, Elsevier, vol. 34(3), pages 896-902.
    6. Liu, Bingwen & Huang, Lihong, 2007. "Existence and exponential stability of almost periodic solutions for cellular neural networks with mixed delays," Chaos, Solitons & Fractals, Elsevier, vol. 32(1), pages 95-103.
    7. Wang, Jian & Lu, Jun Guo, 2008. "Global exponential stability of fuzzy cellular neural networks with delays and reaction–diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 38(3), pages 878-885.
    8. Huang, Zai-Tang & Yang, Qi-Gui & Luo, Xiao-shu, 2008. "Exponential stability of impulsive neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 35(4), pages 770-780.
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    Cited by:

    1. Zhang, Yutian & Luo, Qi, 2012. "Novel stability criteria for impulsive delayed reaction–diffusion Cohen–Grossberg neural networks via Hardy–Poincarè inequality," Chaos, Solitons & Fractals, Elsevier, vol. 45(8), pages 1033-1040.
    2. Long, Shujun & Wang, Xiaohu & Li, Dingshi, 2012. "Attracting and invariant sets of non-autonomous reaction-diffusion neural networks with time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(11), pages 2199-2214.

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