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Global exponential stability of impulsive Cohen–Grossberg neural networks with continuously distributed delays

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  • Ping, Zhao Wu
  • Lu, Jun Guo

Abstract

In this paper, several classes of impulsive Cohen–Grossberg neural networks with continuously distributed delays are considered. Global exponential stability and robust global exponential stability of the equilibrium solution are investigated by using Lyapunov function and integro-differential inequality. Moreover, sufficient conditions are also given to guarantee the existence of ϖ-periodic solution and that all other solutions are convergent to it globally exponentially. Finally, two examples are given to demonstrate the effectiveness of our results in this paper.

Suggested Citation

  • Ping, Zhao Wu & Lu, Jun Guo, 2009. "Global exponential stability of impulsive Cohen–Grossberg neural networks with continuously distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 164-174.
    • Handle: RePEc:eee:chsofr:v:41:y:2009:i:1:p:164-174
    DOI: 10.1016/j.chaos.2007.11.022
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    References listed on IDEAS

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    1. Zhou, Qinghua & Wan, Li & Sun, Jianhua, 2007. "Exponential stability of reaction–diffusion generalized Cohen–Grossberg neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 32(5), pages 1713-1719.
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    8. Huang, Tingwen & Li, Chuandong & Chen, Goong, 2007. "Stability of Cohen–Grossberg neural networks with unbounded distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 34(3), pages 992-996.
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    10. Bai, Chuanzhi, 2008. "Stability analysis of Cohen–Grossberg BAM neural networks with delays and impulses," Chaos, Solitons & Fractals, Elsevier, vol. 35(2), pages 263-267.
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