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Quasi-state estimation and quasi-synchronization control of quaternion-valued fractional-order fuzzy memristive neural networks: Vector ordering approach

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  • Li, Ruoxia
  • Gao, Xingbao
  • Cao, Jinde

Abstract

This paper is dedicated to investigate the quasi-estimation and quasi-synchronization control of the fractional-order fuzzy memristive neural networks. By starting from the quaternion-valued algorithms, a fractional-order quaternion-valued memristive model is obtained, then, through the appropriate controllers, the corresponding quasi-estimation and quasi-synchronization control issues are considered. It is noteworthy that, to derive the corresponding conclusions, the vector ordering approach is employed, thus, one can compare the “magnitude” of two quaternions, and the closed convex hull derived by the quaternion-valued connections can be derived correspondingly. Finally, example is raised to test the proposed scheme.

Suggested Citation

  • Li, Ruoxia & Gao, Xingbao & Cao, Jinde, 2019. "Quasi-state estimation and quasi-synchronization control of quaternion-valued fractional-order fuzzy memristive neural networks: Vector ordering approach," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    • Handle: RePEc:eee:apmaco:v:362:y:2019:i:c:34
    DOI: 10.1016/j.amc.2019.124572
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    References listed on IDEAS

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    1. Zhang, Guodong & Zeng, Zhigang, 2018. "Exponential stability for a class of memristive neural networks with mixed time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 544-554.
    2. Mathiyalagan, K. & Park, Ju H. & Sakthivel, R., 2015. "Synchronization for delayed memristive BAM neural networks using impulsive control with random nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 967-979.
    3. Zhang, Lingzhong & Yang, Yongqing & Wang, Fei, 2017. "Projective synchronization of fractional-order memristive neural networks with switching jumps mismatch," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 402-415.
    4. Li, Ruoxia & Gao, Xingbao & Cao, Jinde, 2019. "Non-fragile state estimation for delayed fractional-order memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 221-233.
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    Cited by:

    1. 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).
    2. Bao, Yuangui & Zhang, Yijun & Zhang, Baoyong, 2021. "Fixed-time synchronization of coupled memristive neural networks via event-triggered control," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    3. Chen, Yonghui & Xue, Yu & Yang, Xiaona & Zhang, Xian, 2023. "A direct analysis method to Lagrangian global exponential stability for quaternion memristive neural networks with mixed delays," Applied Mathematics and Computation, Elsevier, vol. 439(C).
    4. Shu, Jinlong & Wu, Baowei & Xiong, Lianglin, 2022. "Stochastic stability criteria and event-triggered control of delayed Markovian jump quaternion-valued neural networks," Applied Mathematics and Computation, Elsevier, vol. 420(C).
    5. 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).

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