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

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  • Luo, Wenpin
  • Zhong, Shouming
  • Yang, Jun

Abstract

In this paper, a class of Cohen–Grossberg neural networks involving delays and impulsive effects is considered. The analysis exploits a homeomorphism mapping and an appropriate Lyapunov functional, to derive easily verifiable sufficient conditions for convergence to the unique globally exponentially stable equilibrium state. The proposed conditions generalize some previous results in the literature. At last, two numerical examples are worked out to illustrate the effectiveness of our results.

Suggested Citation

  • Luo, Wenpin & Zhong, Shouming & Yang, Jun, 2009. "Global exponential stability of impulsive Cohen–Grossberg neural networks with delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 1084-1091.
  • Handle: RePEc:eee:chsofr:v:42:y:2009:i:2:p:1084-1091
    DOI: 10.1016/j.chaos.2009.03.046
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    References listed on IDEAS

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    1. Xia, Yonghui & Huang, Zhenkun & Han, Maoan, 2008. "Exponential p-stability of delayed Cohen–Grossberg-type BAM neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 38(3), pages 806-818.
    2. Mohamad, Sannay, 2007. "Exponential stability in Hopfield-type neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 32(2), pages 456-467.
    3. 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.
    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.
    5. 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. Qian-hong Zhang & Li-hui Yang, 2012. "Dynamical analysis of fuzzy BAM neural networks with variable delays," Fuzzy Information and Engineering, Springer, vol. 4(1), pages 93-104, March.

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