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Asymptotical stability of multi-delayed cellular neural networks with impulsive effects

Author

Listed:
  • Li, Dong
  • Yang, Dan
  • Wang, Hui
  • Zhang, Xiaohong
  • Wang, Shilong

Abstract

In this work, the stability issues of the equilibrium points of multi-delayed cellular neural networks with impulsive effects are investigated. Based on the method of linear matrix inequality (LMI) and parameterized first-order model transformation, several new delay-dependent and delay-independent asymptotical stability conditions are derived by the stability theory of Lyapunov–Krasovskii. A numerical example is given to illustrate the effectiveness of our results.

Suggested Citation

  • Li, Dong & Yang, Dan & Wang, Hui & Zhang, Xiaohong & Wang, Shilong, 2009. "Asymptotical stability of multi-delayed cellular neural networks with impulsive effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(2), pages 218-224.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:2:p:218-224
    DOI: 10.1016/j.physa.2008.09.025
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    References listed on IDEAS

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    1. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2005. "On global exponential stability of nonautonomous delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 26(3), pages 965-970.
    2. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2005. "Delay-dependent exponential stability of cellular neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 23(4), pages 1363-1369.
    3. Li, Yongkun & Xing, Zhiwei, 2007. "Existence and global exponential stability of periodic solution of CNNs with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 33(5), pages 1686-1693.
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    Cited by:

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    2. Wang, Yuangan & Yu, Honglin, 2018. "Fuzzy synchronization of chaotic systems via intermittent control," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 154-160.

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