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Exponential stability criterion for interval neural networks with discrete and distributed delays

Author

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  • Chen, Hao
  • Zhong, Shouming
  • Shao, Jinliang

Abstract

This paper investigates the global exponential stability of neural networks with discrete and distributed delays. A new criterion for the exponential stability of neural networks with mixed delays is derived by using the Lyapunov stability theory, Homomorphic mapping theory and matrix theory. The obtained result is easier to be verified than those previously reported stability results. Finally, some illustrative numerical examples are given to show the effectiveness of the proposed result.

Suggested Citation

  • Chen, Hao & Zhong, Shouming & Shao, Jinliang, 2015. "Exponential stability criterion for interval neural networks with discrete and distributed delays," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 121-130.
    • Handle: RePEc:eee:apmaco:v:250:y:2015:i:c:p:121-130
    DOI: 10.1016/j.amc.2014.10.089
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    References listed on IDEAS

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    1. Lien, Chang-Hua & Chung, Long-Yeu, 2007. "Global asymptotic stability for cellular neural networks with discrete and distributed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 34(4), pages 1213-1219.
    2. Song, Qiankun & Wang, Zidong, 2008. "Neural networks with discrete and distributed time-varying delays: A general stability analysis," Chaos, Solitons & Fractals, Elsevier, vol. 37(5), pages 1538-1547.
    3. Jun Cheng & Hong Zhu & Shouming Zhong & Yuping Zhang & Yuanyuan Li, 2015. "Finite-time control for a class of discrete-time Markovian jump systems with partly unknown time-varying transition probabilities subject to average dwell time switching," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(6), pages 1080-1093, April.
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    Cited by:

    1. Wang, Lingyu & Huang, Tingwen & Xiao, Qiang, 2018. "Global exponential synchronization of nonautonomous recurrent neural networks with time delays on time scales," Applied Mathematics and Computation, Elsevier, vol. 328(C), pages 263-275.
    2. Zhang, Chuan-Ke & He, Yong & Jiang, Lin & Lin, Wen-Juan & Wu, Min, 2017. "Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix approach," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 102-120.
    3. Mahmoud, Magdi S. & Almutairi, Naif B., 2016. "Feedback fuzzy control for quantized networked systems with random delays," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 80-97.
    4. Liu, Yan & Guo, Ying & Li, Wenxue, 2016. "The stability of stochastic coupled systems with time delays and time-varying coupling structure," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 507-520.
    5. Kumar, Ankit & Das, Subir & Yadav, Vijay K. & Rajeev,, 2021. "Global quasi-synchronization of complex-valued recurrent neural networks with time-varying delay and interaction terms," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).

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