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Exponential convergence rate estimation for uncertain delayed neural networks of neutral type

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  • Lien, Chang-Hua
  • Yu, Ker-Wei
  • Lin, Yen-Feng
  • Chung, Yeong-Jay
  • Chung, Long-Yeu

Abstract

The global exponential stability for a class of uncertain delayed neural networks (DNNs) of neutral type is investigated in this paper. Delay-dependent and delay-independent criteria are proposed to guarantee the robust stability of DNNs via LMI and Razumikhin-like approaches. For a given delay, the maximal allowable exponential convergence rate will be estimated. Some numerical examples are given to illustrate the effectiveness of our results. The simulation results reveal significant improvement over the recent results.

Suggested Citation

  • Lien, Chang-Hua & Yu, Ker-Wei & Lin, Yen-Feng & Chung, Yeong-Jay & Chung, Long-Yeu, 2009. "Exponential convergence rate estimation for uncertain delayed neural networks of neutral type," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2491-2499.
    • Handle: RePEc:eee:chsofr:v:40:y:2009:i:5:p:2491-2499
    DOI: 10.1016/j.chaos.2007.10.043
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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. Li, Chuandong & Liao, Xiaofeng & Zhang, Rong & Prasad, Ashutosh, 2005. "Global robust exponential stability analysis for interval neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 25(3), pages 751-757.
    3. Zhang, Qiang & Xu, Xiaopeng Wei Jin, 2007. "Delay-dependent global stability results for delayed Hopfield neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 662-668.
    4. 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.
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