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Input-to-State stability analysis for memristive Cohen-Grossberg-type neural networks with variable time delays

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  • Zhao, Yong
  • Kurths, Jürgen
  • Duan, Lixia

Abstract

In this paper, we discussed the input-to-state stability of a class of memristive Cohen–Grossberg-type neural networks with variable time delays. Based on a nonsmooth analysis and set-valued maps, some novel sufficient conditions are obtained for the input-to-state stability of such networks, which include some known results as particular cases. Especially, when the input is zero, it reduced to asymptotical stability of the state. Finally, an illustrative example is presented to illustrate the feasibility and effectiveness of our results.

Suggested Citation

  • Zhao, Yong & Kurths, Jürgen & Duan, Lixia, 2018. "Input-to-State stability analysis for memristive Cohen-Grossberg-type neural networks with variable time delays," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 364-369.
  • Handle: RePEc:eee:chsofr:v:114:y:2018:i:c:p:364-369
    DOI: 10.1016/j.chaos.2018.07.021
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    References listed on IDEAS

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    1. Zhang, Chaolong & Deng, Feiqi & Peng, Yunjian & Zhang, Bo, 2015. "Adaptive synchronization of Cohen–Grossberg neural network with mixed time-varying delays and stochastic perturbation," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 792-801.
    2. Robert Legenstein, 2015. "Nanoscale connections for brain-like circuits," Nature, Nature, vol. 521(7550), pages 37-38, May.
    3. Dmitri B. Strukov & Gregory S. Snider & Duncan R. Stewart & R. Stanley Williams, 2008. "The missing memristor found," Nature, Nature, vol. 453(7191), pages 80-83, May.
    4. Li, Yongkun, 2005. "Global exponential stability of BAM neural networks with delays and impulses," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 279-285.
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    Cited by:

    1. Xiang, Jianglian & Ren, Junwu & Tan, Manchun, 2022. "Stability analysis for memristor-based stochastic multi-layer neural networks with coupling disturbance," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).

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