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Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays

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  • Zhang, Ruimei
  • Zeng, Deqiang
  • Zhong, Shouming
  • Yu, Yongbin

Abstract

This paper investigates the global asymptotic stability and stabilization of memristive neural networks (MNNs) with communication delays via event-triggered sampling control. First, based on the novel approach in Lemma 1, the concerned MNNs are converted into traditional neural networks with uncertain parameters. Next, a discrete event-triggered sampling control scheme, which only needs supervision of the system state at discrete instants, is designed for MNNs for the first time. Thanks to this controller, the number of control updates could greatly reduce. Then, by getting utmost out of the usable information on the actual sampling pattern, a newly augmented Lyapunov-Krasovskii functional (LKF) is constructed to formulate stability and stabilization criteria. It should be mentioned that the LKF is positive definite only at endpoints of each subinterval of the holding intervals but not necessarily positive definite inside the holding intervals. Finally, the feasibility and effectiveness of the proposed results are tested by two numerical examples.

Suggested Citation

  • Zhang, Ruimei & Zeng, Deqiang & Zhong, Shouming & Yu, Yongbin, 2017. "Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 57-74.
  • Handle: RePEc:eee:apmaco:v:310:y:2017:i:c:p:57-74
    DOI: 10.1016/j.amc.2017.04.028
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    References listed on IDEAS

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    1. Zhou, Jiamu & Dong, Hailing & Feng, Jianwen, 2017. "Event-triggered communication for synchronization of Markovian jump delayed complex networks with partially unknown transition rates," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 617-629.
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    4. 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.
    5. Sakthivel, R. & Anbuvithya, R. & Mathiyalagan, K. & Ma, Yong-Ki & Prakash, P., 2016. "Reliable anti-synchronization conditions for BAM memristive neural networks with different memductance functions," Applied Mathematics and Computation, Elsevier, vol. 275(C), pages 213-228.
    6. Li, Ruoxia & Cao, Jinde, 2016. "Stability analysis of reaction-diffusion uncertain memristive neural networks with time-varying delays and leakage term," Applied Mathematics and Computation, Elsevier, vol. 278(C), pages 54-69.
    7. Xu, Qiyi & Zhang, Yijun & He, Wangli & Xiao, Shunyuan, 2017. "Event-triggered networked H∞ control of discrete-time nonlinear singular systems," Applied Mathematics and Computation, Elsevier, vol. 298(C), pages 368-382.
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