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Novel LMI condition for global robust stability of delayed neural networks

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  • Singh, Vimal

Abstract

A novel criterion for the uniqueness and global robust stability of the equilibrium point of Hopfield-type neural networks with delay is presented. The criterion takes the form of a linear matrix inequality and hence is computationally attractive. An example showing the effectiveness of the present approach is given.

Suggested Citation

  • Singh, Vimal, 2007. "Novel LMI condition for global robust stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 503-508.
    • Handle: RePEc:eee:chsofr:v:34:y:2007:i:2:p:503-508
    DOI: 10.1016/j.chaos.2006.03.034
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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.
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    9. Zhu, Wenli & Hu, Jin, 2006. "Stability analysis of stochastic delayed cellular neural networks by LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 29(1), pages 171-174.
    10. 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.
    11. Singh, Vimal, 2006. "Simplified LMI condition for global asymptotic stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 29(2), pages 470-473.
    12. Hu, Jin & Zhong, Shouming & Liang, Li, 2006. "Exponential stability analysis of stochastic delayed cellular neural network," Chaos, Solitons & Fractals, Elsevier, vol. 27(4), pages 1006-1010.
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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. Singh, Vimal, 2009. "Novel global robust stability criterion for neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 348-353.
    3. Yucel, Eylem & Arik, Sabri, 2009. "Novel results for global robust stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 39(4), pages 1604-1614.
    4. 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.
    5. Sheng, Li & Yang, Huizhong, 2009. "Robust stability of uncertain Markovian jumping Cohen–Grossberg neural networks with mixed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2120-2128.

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