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Finite-time stabilization for delayed quaternion-valued coupled neural networks with saturated impulse

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  • Chen, Yuan
  • Wu, Jianwei
  • Bao, Haibo

Abstract

In this paper, finite-time stabilization (FTS) issue of delayed quaternion-valued coupled neural networks (DQVCNNs) with saturated impulse is discussed for the first time. Saturated impulse, time-varying delay and quaternion are first considered into coupled neural networks (CNNs), which makes the model more complex and realistic. Secondly, a hybrid feedback controller is designed, some conditions are derived to stabilize DQVCNNs with saturated impulse in finite time by the idea of polytopic representation and sector nonlinearity model, respectively. Furthermore, this paper shows the settling-time of DQVCNNs with saturated impulse, which discloses it related to both impulse and initial state. Next, this paper also presents several corresponding essential corollaries. Lastly, the feasibility of the derived results is further explained by two examples.

Suggested Citation

  • Chen, Yuan & Wu, Jianwei & Bao, Haibo, 2022. "Finite-time stabilization for delayed quaternion-valued coupled neural networks with saturated impulse," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    • Handle: RePEc:eee:apmaco:v:425:y:2022:i:c:s0096300322001679
    DOI: 10.1016/j.amc.2022.127083
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    References listed on IDEAS

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    1. Zhang, Lan & Yang, Xinsong & Xu, Chen & Feng, Jianwen, 2017. "Exponential synchronization of complex-valued complex networks with time-varying delays and stochastic perturbations via time-delayed impulsive control," Applied Mathematics and Computation, Elsevier, vol. 306(C), pages 22-30.
    2. Lin, Dongyuan & Chen, Xiaofeng & Yu, Guoping & Li, Zhongshan & Xia, Yannan, 2021. "Global exponential synchronization via nonlinear feedback control for delayed inertial memristor-based quaternion-valued neural networks with impulses," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    3. Qi, Xingnan & Bao, Haibo & Cao, Jinde, 2019. "Exponential input-to-state stability of quaternion-valued neural networks with time delay," Applied Mathematics and Computation, Elsevier, vol. 358(C), pages 382-393.
    4. Zhou, Ya & Wan, Xiaoxiao & Huang, Chuangxia & Yang, Xinsong, 2020. "Finite-time stochastic synchronization of dynamic networks with nonlinear coupling strength via quantized intermittent control," Applied Mathematics and Computation, Elsevier, vol. 376(C).
    5. Feng, Yuming & Yang, Xinsong & Song, Qiang & Cao, Jinde, 2018. "Synchronization of memristive neural networks with mixed delays via quantized intermittent control," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 874-887.
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    Cited by:

    1. Zhang, Guodong & Cao, Jinde, 2023. "New results on fixed/predefined-time synchronization of delayed fuzzy inertial discontinuous neural networks: Non-reduced order approach," Applied Mathematics and Computation, Elsevier, vol. 440(C).
    2. Mo, Wenjun & Bao, Haibo, 2022. "Finite-time synchronization for fractional-order quaternion-valued coupled neural networks with saturated impulse," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    3. Cui, Xueke & Li, Hong-Li & Zhang, Long & Hu, Cheng & Bao, Haibo, 2023. "Complete synchronization for discrete-time fractional-order coupled neural networks with time delays," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    4. Yang, Dongsheng & Yu, Yongguang & Wang, Hu & Ren, Guojian & Zhang, Xiaoli, 2024. "Successive lag synchronization of heterogeneous distributed-order coupled neural networks with unbounded delayed coupling," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

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