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Robust exponential stability of interval Cohen–Grossberg neural networks with time-varying delays

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  • Gao, Ming
  • Cui, Baotong

Abstract

In this paper, the problem of robust exponential stability for a class of interval Cohen–Grossberg neural networks with time-varying delays is investigated. Without assuming the boundedness and differentiability of the activation functions and any symmetry of interconnection matrices, some sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point are derived. Some comparisons between the results presented in this paper and the previous results admit that our results are the improvement and extension of the existed ones. The validity and performance of the new results are further illustrated by two simulation examples.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:chsofr:v:40:y:2009:i:4:p:1914-1928
    DOI: 10.1016/j.chaos.2007.09.072
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    References listed on IDEAS

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    1. Arik, Sabri, 2005. "Global robust stability analysis of neural networks with discrete time delays," Chaos, Solitons & Fractals, Elsevier, vol. 26(5), pages 1407-1414.
    2. Wu, Wei & Cui, Bao Tong & Huang, Min, 2007. "Global asymptotic stability of Cohen–Grossberg neural networks with constant and variable delays," Chaos, Solitons & Fractals, Elsevier, vol. 33(4), pages 1355-1361.
    3. Wu, Wei & Cui, Bao Tong, 2008. "Global robust exponential stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 35(4), pages 747-754.
    4. Lou, Xuyang & Cui, Baotong, 2007. "Boundedness and exponential stability for nonautonomous cellular neural networks with reaction–diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 33(2), pages 653-662.
    5. 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.
    6. Lou, Xuyang & Cui, Baotong, 2007. "Absolute exponential stability analysis of delayed bi-directional associative memory neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 31(3), pages 695-701.
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    Cited by:

    1. Lan, Heng-you & Cui, Yi-Shun, 2009. "A neural network method for solving a system of linear variational inequalities," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1245-1252.
    2. 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.
    3. Bao, Gang & Zeng, Zhigang, 2021. "Prescribed convergence analysis of recurrent neural networks with parameter variations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 858-870.

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