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Delay-dependent stability criterion for delayed Hopfield neural networks

Author

Listed:
  • Jiang, Yanhong
  • Yang, Bin
  • Wang, Jincheng
  • Shao, Cheng

Abstract

In this paper, a new Lyapunov–Krasovskii functional is constructed for delayed Hopfield neural networks, and several free-weighting matrices and S-procedure are employed to derive the delay-dependent stability criterion. The derived criterion is formulated in terms of linear matrix inequality (LMI). A numerical example is given to demonstrate the effectiveness and less conservativeness of the presented criterion.

Suggested Citation

  • Jiang, Yanhong & Yang, Bin & Wang, Jincheng & Shao, Cheng, 2009. "Delay-dependent stability criterion for delayed Hopfield neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 39(5), pages 2133-2137.
    • Handle: RePEc:eee:chsofr:v:39:y:2009:i:5:p:2133-2137
    DOI: 10.1016/j.chaos.2007.06.039
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    References listed on IDEAS

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    1. Cao, Jinde & Ho, Daniel W.C., 2005. "A general framework for global asymptotic stability analysis of delayed neural networks based on LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 24(5), pages 1317-1329.
    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. Park, Ju H., 2006. "On global stability criterion for neural networks with discrete and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 30(4), pages 897-902.
    4. Cheng, Chao-Jung & Liao, Teh-Lu & Hwang, Chi-Chuan, 2005. "Exponential synchronization of a class of chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 197-206.
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