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On Global Exponential Stability of Discrete-Time Hopfield Neural Networks with Variable Delays

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  • Qiang Zhang
  • Xiaopeng Wei
  • Jin Xu

Abstract

Global exponential stability of a class of discrete-time Hopfield neural networks with variable delays is considered. By making use of a difference inequality, a new global exponential stability result is provided. The result only requires the delay to be bounded. For this reason, the result is milder than those presented in the earlier references. Furthermore, two examples are given to show the efficiency of our result.

Suggested Citation

  • Qiang Zhang & Xiaopeng Wei & Jin Xu, 2007. "On Global Exponential Stability of Discrete-Time Hopfield Neural Networks with Variable Delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2007, pages 1-9, April.
    • Handle: RePEc:hin:jnddns:067675
    DOI: 10.1155/2007/67675
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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.
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    Cited by:

    1. Suntonsinsoungvon, E. & Udpin, S., 2020. "Exponential stability of discrete-time uncertain neural networks with multiple time-varying leakage delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 233-245.

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