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An event-triggered synchronization of semi-Markov jump neural networks with time-varying delays based on generalized free-weighting-matrix approach

Author

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  • Pradeep, C.
  • Cao, Yang
  • Murugesu, R.
  • Rakkiyappan, R.

Abstract

In this paper, synchronization results for semi-Markovian jump neural networks with time-varying delays are investigated based on the event-triggered control scheme. With the construction of suitable Lyapunov–Krasovskii functional (LKF), novel synchronization criteria for delayed semi-Markovian jump neural networks are established in the form of linear matrix inequalities (LMIs). Rather, a general free-weighting matrix approach, which is proven to produce less conservative results than the existing methods, is employed to estimate the single integral term. The desired synchronization is achieved by solving the obtained set of LMIs. Eventually, numerical examples are proposed to show the validity of the proposed approach.

Suggested Citation

  • Pradeep, C. & Cao, Yang & Murugesu, R. & Rakkiyappan, R., 2019. "An event-triggered synchronization of semi-Markov jump neural networks with time-varying delays based on generalized free-weighting-matrix approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 41-56.
    • Handle: RePEc:eee:matcom:v:155:y:2019:i:c:p:41-56
    DOI: 10.1016/j.matcom.2017.11.001
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Hongmei & Cao, Jinde & Xiong, Lianglin, 2019. "Novel synchronization conditions for time-varying delayed Lur’e system with parametric uncertainty," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 224-236.
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    4. Song, Xingxing & Lu, Hongqian & Xu, Yao & Zhou, Wuneng, 2022. "H∞ synchronization of semi-Markovian jump neural networks with random sensor nonlinearities via adaptive event-triggered output feedback control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 198(C), pages 1-19.
    5. Li, Liangchen & Xu, Rui & Lin, Jiazhe, 2020. "Lagrange stability for uncertain memristive neural networks with Lévy noise and leakage delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    6. Liu, Jixin & Song, Shimin & Jiang, Haijun & Li, Jiarong & Liu, Xiaolin, 2020. "New results of projective synchronization for memristor-based coupled neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    7. Wang, Yao & Guo, Jun & Liu, Guobao & Lu, Junwei & Li, Fangyuan, 2021. "Finite-time sampled-data synchronization for uncertain neutral-type semi-Markovian jump neural networks with mixed time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    8. Guo, Beibei & Xiao, Yu & Zhang, Chiping & Zhao, Yong, 2020. "Graph theory-based adaptive intermittent synchronization for stochastic delayed complex networks with semi-Markov jump," Applied Mathematics and Computation, Elsevier, vol. 366(C).

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