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New robust stability criteria for uncertain neural networks with interval time-varying delays

Author

Listed:
  • Qiu, Jiqing
  • Yang, Hongjiu
  • Zhang, Jinhui
  • Gao, Zhifeng

Abstract

In this paper, problem of robust stability of uncertain neural networks with interval time-varying delays has been investigated. The delay factor is assumed to be time-varying and belongs to a given interval, which means that the lower and upper bounds of the interval time-varying delays are available. Based on the Lyapunov–Krasovskii functional approach, a new delay-dependent stability criteria is presented in terms of linear matrix inequalities (LMIs). Two numerical examples are given to illustrate the effectiveness of the proposed method.

Suggested Citation

  • Qiu, Jiqing & Yang, Hongjiu & Zhang, Jinhui & Gao, Zhifeng, 2009. "New robust stability criteria for uncertain neural networks with interval time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 39(2), pages 579-585.
    • Handle: RePEc:eee:chsofr:v:39:y:2009:i:2:p:579-585
    DOI: 10.1016/j.chaos.2007.01.087
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    References listed on IDEAS

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    1. 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.
    2. Zhang, Hongbin & Li, Chunguang & Liao, Xiaofeng, 2005. "A note on the robust stability of neural networks with time delay," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 357-360.
    3. He, Yong & Wang, Qing-Guo & Zheng, Wei-Xing, 2005. "Global robust stability for delayed neural networks with polytopic type uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 26(5), pages 1349-1354.
    4. Yang, Haifeng & Chu, Tianguang & Zhang, Cishen, 2006. "Exponential stability of neural networks with variable delays via LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 30(1), pages 133-139.
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    Cited by:

    1. Park, Ju H. & Kwon, O.M., 2009. "Global stability for neural networks of neutral-type with interval time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1174-1181.
    2. Zhang, Zhongjie & Yu, Tingting & Zhang, Xian, 2022. "Algebra criteria for global exponential stability of multiple time-varying delay Cohen–Grossberg neural networks," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    3. Maharajan, C. & Raja, R. & Cao, Jinde & Rajchakit, G. & Alsaedi, Ahmed, 2018. "Novel results on passivity and exponential passivity for multiple discrete delayed neutral-type neural networks with leakage and distributed time-delays," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 268-282.

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