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Global robust exponential stability of delayed neural networks

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  • Wu, Wei
  • Cui, Bao Tong

Abstract

In this paper, the global robust exponential stability of interval neural networks with time delays is investigated. As far as we are aware only, few papers deals with the interval neural networks and focus on the robust exponential stability. A linear matrix inequality (LMI) approach is developed to derive sufficient conditions ensuring the delayed neural network to have a unique equilibrium point, which is globally robust exponentially stable. The proposed LMI conditions can be checked easily by a recently developed algorithms solving LMIs.

Suggested Citation

  • Wu, Wei & Cui, Bao Tong, 2008. "Global robust exponential stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 35(4), pages 747-754.
    • Handle: RePEc:eee:chsofr:v:35:y:2008:i:4:p:747-754
    DOI: 10.1016/j.chaos.2006.05.096
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    References listed on IDEAS

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    1. Cui, Bao Tong & Lou, Xu Yang, 2006. "Global asymptotic stability of BAM neural networks with distributed delays and reaction–diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 27(5), pages 1347-1354.
    2. Lou, Xu Yang & Cui, Bao Tong, 2006. "Global asymptotic stability of delay BAM neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 29(4), pages 1023-1031.
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    Cited by:

    1. Cui, Shihua & Zhao, Tao & Guo, Jie, 2009. "Global robust exponential stability for interval neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1567-1576.
    2. Sheng, Li & Yang, Huizhong, 2009. "Novel global robust exponential stability criterion for uncertain BAM neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2102-2113.
    3. Tian, Junkang & Xu, Dongsheng, 2009. "New asymptotic stability criteria for neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 1916-1922.
    4. Gao, Ming & Cui, Baotong, 2009. "Robust exponential stability of interval Cohen–Grossberg neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1914-1928.

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