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New Criterias of Synchronization for Discrete-Time Recurrent Neural Networks with Time-Varying Delay via Event-Triggered Control

Author

Listed:
  • Lei Yu

    (College of Sciences, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Guici Chen

    (College of Sciences, Wuhan University of Science and Technology, Wuhan 430065, China
    Hubei Province Key Laboratory of System Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Feng Jiang

    (School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan 430073, China)

  • Zhi Wang

    (School of Sciences, Ningbo University of Technology, 201 Fenghua Rd., Ningbo 315211, China)

Abstract

This paper mainly researches the synchronization issue of discrete-time recurrent neural networks (DTRNNs) with time-varying delay based on event-triggered control (ETC). ETC can effectively decrease the quantity of controller updates performed and the utilization of communication resources. By using Lyapunov–Krasovskii functional (LKF), Schur complement lemma, discrete time free weight matrix method, linear matrix inequalities (LMIs) and other analytical methods, the stability conditions of the error system are deduced. Accordingly, a class of event-triggered state feedback controllers is designed. Finally, through two numerical examples with simulations, the effectiveness of the controller is verified.

Suggested Citation

  • Lei Yu & Guici Chen & Feng Jiang & Zhi Wang, 2022. "New Criterias of Synchronization for Discrete-Time Recurrent Neural Networks with Time-Varying Delay via Event-Triggered Control," Mathematics, MDPI, vol. 10(15), pages 1-17, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:15:p:2816-:d:883288
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    References listed on IDEAS

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    1. Chen, Guici & Gao, Yu & Zhu, Shasha, 2017. "Finite-time dissipative control for stochastic interval systems with time-delay and Markovian switching," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 169-181.
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