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Projective synchronization in finite-time for fully quaternion-valued memristive networks with fractional-order

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  • Yang, Shuai
  • Hu, Cheng
  • Yu, Juan
  • Jiang, Haijun

Abstract

Based on the non-separation method, the finite-time projective synchronization of fractional-order quaternion-valued memristive networks with discontinuous activation functions is investigated in this paper. Firstly, the sign function related to quaternion is introduced and some properties concerning it are developed. Secondly, two different quaternion-valued controllers are designed by feat of the proposed sign function. Subsequently, several synchronization conditions are derived and the settling times are evaluated validly by the established finite-time fractional-order inequality. Especially noteworthy is that the addressed networks are converted into systems with parametric uncertainty in the framework of differential inclusion and measurable selection. Finally, a numerical example is given to demonstrate the correctness of theoretical analyses.

Suggested Citation

  • Yang, Shuai & Hu, Cheng & Yu, Juan & Jiang, Haijun, 2021. "Projective synchronization in finite-time for fully quaternion-valued memristive networks with fractional-order," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:chsofr:v:147:y:2021:i:c:s0960077921002654
    DOI: 10.1016/j.chaos.2021.110911
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    References listed on IDEAS

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    Cited by:

    1. Xiong, Kailong & Hu, Cheng & Yu, Juan, 2023. "Direct approach-based synchronization of fully quaternion-valued neural networks with inertial term and time-varying delay," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    2. He, Jin-Man & Pei, Li-Jun, 2023. "Function matrix projection synchronization for the multi-time delayed fractional order memristor-based neural networks with parameter uncertainty," Applied Mathematics and Computation, Elsevier, vol. 454(C).
    3. 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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