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Robust state estimation for fractional-order complex-valued delayed neural networks with interval parameter uncertainties: LMI approach

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  • Hu, Binxin
  • Song, Qiankun
  • Zhao, Zhenjiang

Abstract

Without separating complex-valued neural networks into two real-valued systems, the state estimation of fractional-order complex-valued neural networks (FCNNs) with uncertain parameters and time delay is investigated in this paper. Based on Lyapunov-Krasovskii functional approach, a new linear matrix inequality (LMI) criterion is derived for asymptotic stability of the estimation error system. A numerical example with simulations is given to confirm the feasibility and availability of the raised result.

Suggested Citation

  • Hu, Binxin & Song, Qiankun & Zhao, Zhenjiang, 2020. "Robust state estimation for fractional-order complex-valued delayed neural networks with interval parameter uncertainties: LMI approach," Applied Mathematics and Computation, Elsevier, vol. 373(C).
    • Handle: RePEc:eee:apmaco:v:373:y:2020:i:c:s0096300320300023
    DOI: 10.1016/j.amc.2020.125033
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    References listed on IDEAS

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    Cited by:

    1. Yaning Yu & Ziye Zhang, 2022. "State Estimation for Complex-Valued Inertial Neural Networks with Multiple Time Delays," Mathematics, MDPI, vol. 10(10), pages 1-14, May.
    2. Thoiyab, N. Mohamed & Muruganantham, P. & Zhu, Quanxin & Gunasekaran, Nallappan, 2021. "Novel results on global stability analysis for multiple time-delayed BAM neural networks under parameter uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    3. Li, Ruoxia & Cao, Jinde & Xue, Changfeng & Manivannan, R., 2021. "Quasi-stability and quasi-synchronization control of quaternion-valued fractional-order discrete-time memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 395(C).
    4. Guo, Ying & Li, Yuze, 2022. "Bipartite leader-following synchronization of fractional-order delayed multilayer signed networks by adaptive and impulsive controllers," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    5. Zhu, Zhen & Lu, Jun-Guo, 2021. "Robust stability and stabilization of hybrid fractional-order multi-dimensional systems with interval uncertainties: An LMI approach," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    6. Udhayakumar, K. & Rakkiyappan, R. & Li, Xiaodi & Cao, Jinde, 2021. "Mutiple ψ-type stability of fractional-order quaternion-valued neural networks," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    7. Li, Qiang & Liang, Jinling, 2022. "Non-fragile asynchronous state estimation for Markovian switching CVNs with partly accessible mode detection: The discrete-time case," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    8. Deng, Jie & Li, Hong-Li & Cao, Jinde & Hu, Cheng & Jiang, Haijun, 2023. "State estimation for discrete-time fractional-order neural networks with time-varying delays and uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    9. Zhang, Hai & Chen, Xinbin & Ye, Renyu & Stamova, Ivanka & Cao, Jinde, 2023. "Adaptive quasi-synchronization analysis for Caputo delayed Cohen–Grossberg neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 49-65.
    10. Wang, Shuzhan & Zhang, Ziye & Lin, Chong & Chen, Jian, 2021. "Fixed-time synchronization for complex-valued BAM neural networks with time-varying delays via pinning control and adaptive pinning control," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).

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