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Global quasi-synchronization of complex-valued recurrent neural networks with time-varying delay and interaction terms

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  • Kumar, Ankit
  • Das, Subir
  • Yadav, Vijay K.
  • Rajeev,

Abstract

In this article, the global quasi-synchronization of complex-valued recurrent neural networks (CVRNNs) with time-varying delays and interaction terms has been investigated. It is based on the standard Lyapunov stability theory and matrix measure method employed with the nonlinear Lipschitz activation functions. A sufficient condition for global quasi-synchronization of the complex-valued recurrent neural network model is shown in an effective way through a proper description of Lyapunov-stability technique. This article provides quite a new result for the CVRNNs having time-varying delays and interaction terms. Finally, a numerical example is considered to show the viability and unwavering quality of our theoretical results under several conditions.

Suggested Citation

  • Kumar, Ankit & Das, Subir & Yadav, Vijay K. & Rajeev,, 2021. "Global quasi-synchronization of complex-valued recurrent neural networks with time-varying delay and interaction terms," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    • Handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921006779
    DOI: 10.1016/j.chaos.2021.111323
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    References listed on IDEAS

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    Cited by:

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    2. Xiong, Kailong & Yu, Juan & Hu, Cheng & Wen, Shiping & Kong, Fanchao, 2024. "Nonseparation analysis-based finite/fixed-time synchronization of fully complex-valued impulsive dynamical networks," Applied Mathematics and Computation, Elsevier, vol. 467(C).
    3. 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.
    4. Kumar, Ankit & Das, Subir & Singh, Sunny & Rajeev,, 2023. "Quasi-projective synchronization of inertial complex-valued recurrent neural networks with mixed time-varying delay and mismatched parameters," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    5. Shi, Lingna & Li, Jiarong & Jiang, Haijun & Wang, Jinling, 2023. "Quasi-synchronization of multi-layer delayed neural networks with parameter mismatches via impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    6. Sun, Wenjing & Tang, Ze & Feng, Jianwen & Park, Ju H., 2024. "Quasi-synchronization of heterogeneous neural networks with hybrid time delays via sampled-data saturating impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

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