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Adaptive quaternion projective synchronization of fractional order delayed neural networks in quaternion field

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  • Zhang, Weiwei
  • Sha, Chunlin
  • Cao, Jinde
  • Wang, Guanglan
  • Wang, Yuan

Abstract

This paper focuses on investigating quaternion projective synchronization of the fractional order delayed quaternion valued neural networks(FODQVNN). By applying Lyapunov direct method rather than decomposition method, quaternion projective synchronization of FODQVNN is discussed, in which the projective coefficient is set to quaternion number. Through designing appropriate adaptive controllers, some succinct criteria ascertaining the quaternion projective synchronization issues for considering systems are obtained. Finally, an example is presented to test the effectiveness of the theoretical scheme.

Suggested Citation

  • Zhang, Weiwei & Sha, Chunlin & Cao, Jinde & Wang, Guanglan & Wang, Yuan, 2021. "Adaptive quaternion projective synchronization of fractional order delayed neural networks in quaternion field," Applied Mathematics and Computation, Elsevier, vol. 400(C).
    • Handle: RePEc:eee:apmaco:v:400:y:2021:i:c:s009630032100093x
    DOI: 10.1016/j.amc.2021.126045
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    References listed on IDEAS

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    2. Liang, Song & Wu, Ranchao & Chen, Liping, 2016. "Adaptive pinning synchronization in fractional-order uncertain complex dynamical networks with delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 49-62.
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    4. Deng, Hui & Bao, Haibo, 2019. "Fixed-time synchronization of quaternion-valued neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    5. Zhang, Weiwei & Cao, Jinde & Wu, Ranchao & Chen, Dingyuan & Alsaadi, Fuad E., 2018. "Novel results on projective synchronization of fractional-order neural networks with multiple time delays," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 76-83.
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    Cited by:

    1. Zheng, Yi & Wu, Xiaoqun & Fan, Ziye & Wang, Wei, 2022. "Identifying topology and system parameters of fractional-order complex dynamical networks," Applied Mathematics and Computation, Elsevier, vol. 414(C).
    2. 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).
    3. Zheng, Bibo & Wang, Zhanshan, 2022. "Mittag-Leffler synchronization of fractional-order coupled neural networks with mixed delays," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    4. Shang, Weiying & Zhang, Weiwei & Chen, Dingyuan & Cao, Jinde, 2023. "New criteria of finite time synchronization of fractional-order quaternion-valued neural networks with time delay," Applied Mathematics and Computation, Elsevier, vol. 436(C).
    5. Zhenduo Sun & Nengneng Qing & Xiangzhi Kong, 2023. "Asymptotic Hybrid Projection Lag Synchronization of Nonidentical Variable-Order Fractional Complex Dynamic Networks," Mathematics, MDPI, vol. 11(13), pages 1-17, June.

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