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Periodic solutions of nonautonomous cellular neural networks with impulses

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  • Gui, Zhanji
  • Ge, Weigao

Abstract

Sufficient conditions are obtained for the existence and global exponential stability of a unique periodic solution of a class of neural networks with impulses by using Mawhin’s continuation theorem of coincidence degree theory and constructing Lyapunov functions. An illustrative example is given to demonstrate the effectiveness of the obtained results.

Suggested Citation

  • Gui, Zhanji & Ge, Weigao, 2007. "Periodic solutions of nonautonomous cellular neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 32(5), pages 1760-1771.
    • Handle: RePEc:eee:chsofr:v:32:y:2007:i:5:p:1760-1771
    DOI: 10.1016/j.chaos.2005.12.001
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    References listed on IDEAS

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    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.
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    6. Li, Yongkun & Xing, Wenya & Lu, Linghong, 2006. "Existence and global exponential stability of periodic solution of a class of neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 27(2), pages 437-445.
    7. Li, Yongkun, 2005. "Global exponential stability of BAM neural networks with delays and impulses," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 279-285.
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    Cited by:

    1. Sun, Jitao & Wang, Qing-Guo & Gao, Hanqiao, 2009. "Periodic solution for nonautonomous cellular neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1423-1427.
    2. Sun, Yeong-Jeu, 2009. "Global exponential stability criterion for uncertain discrete-time cellular neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 2022-2024.

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