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Synchronization of multi-link and multi-delayed inertial neural networks with Markov jump via aperiodically intermittent adaptive control

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  • Guo, Beibei
  • Xiao, Yu

Abstract

In this paper, we investigate the exponential synchronization problem for multi-link and multi-delayed inertial neural networks with Markov jump (MMDINNMJ) using an aperiodically intermittent adaptive control strategy. Different from most research on inertial neural networks, we take multi-link, multi-delay and Markov jump into account. The obstacle caused by the coexistence of Markov jump and multi-delay is avoided by using the delayed integral method while considering the exponential synchronization of MMDINNMJ. Additionally, under graph theory, Lyapunov stability theory and the developed control scheme, some novel sufficient conditions for synchronization at exponential rate in pth (p>0) moment of underlying networks are determined, which are strongly related to multi-link topological structure, time delay, and Markov jump. Finally, two examples are given to demonstrate the viability of the theoretical conclusions.

Suggested Citation

  • Guo, Beibei & Xiao, Yu, 2024. "Synchronization of multi-link and multi-delayed inertial neural networks with Markov jump via aperiodically intermittent adaptive control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 219(C), pages 435-453.
    • Handle: RePEc:eee:matcom:v:219:y:2024:i:c:p:435-453
    DOI: 10.1016/j.matcom.2023.12.039
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    References listed on IDEAS

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    Cited by:

    1. Tang, Zeshen & Liu, Xiwei, 2024. "Synchronization of directly coupled complex networks with multiweights and multiple delays," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).
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    3. Rakkiyappan, R. & Sharmila, V. & Janani, K. & Kashkynbayev, Ardak, 2024. "Stabilization of Takagi–Sugeno fuzzy Hidden Markov Jump Systems with memory sampled-data control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 226(C), pages 204-217.

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