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Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays

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  • Ziye Zhang
  • Xiaoping Liu
  • Chong Lin
  • Bing Chen

Abstract

This paper focuses on the finite-time synchronization analysis for complex-valued recurrent neural networks with time delays. First, two kinds of common activation functions appearing in the existing references are combined together and more general assumptions are given. To achieve our aim, a nonlinear delayed controller with two independent parameters different from the existing ones is provided, which leads to great difficulty. To overcome it, a newly developed inequality is used. Then, via Lyapunov function approach, some criteria are derived to guarantee the finite-time synchronization of the considered system, and the settling time for synchronization is also estimated. Finally, two numerical simulations are given to support the effectiveness and advantages of the obtained results.

Suggested Citation

  • Ziye Zhang & Xiaoping Liu & Chong Lin & Bing Chen, 2018. "Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays," Complexity, Hindawi, vol. 2018, pages 1-14, December.
    • Handle: RePEc:hin:complx:8456737
    DOI: 10.1155/2018/8456737
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    References listed on IDEAS

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    6. Jiao, Shiyu & Shen, Hao & Wei, Yunliang & Huang, Xia & Wang, Zhen, 2018. "Further results on dissipativity and stability analysis of Markov jump generalized neural networks with time-varying interval delays," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 338-350.
    7. Shaowei Zhou & Xiaoping Liu & Bing Chen & Hongxia Liu, 2018. "Stability Analysis for a Class of Discrete-Time Nonhomogeneous Markov Jump Systems with Multiplicative Noises," Complexity, Hindawi, vol. 2018, pages 1-9, February.
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    Cited by:

    1. Luo, Mengzhuo & Liu, Xinzhi & Zhong, Shouming & Cheng, Jun, 2018. "Synchronization of stochastic complex networks with discrete-time and distributed coupling delayed via hybrid nonlinear and impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 381-393.
    2. Chen, Dazhao & Zhang, Zhengqiu, 2022. "Finite-time synchronization for delayed BAM neural networks by the approach of the same structural functions," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    3. Qin, Xiaoli & Wang, Cong & Li, Lixiang & Peng, Haipeng & Yang, Yixian & Ye, Lu, 2018. "Finite-time modified projective synchronization of memristor-based neural network with multi-links and leakage delay," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 302-315.
    4. Zhen Yang & Zhengqiu Zhang, 2023. "New Results on Finite-Time Synchronization of Complex-Valued BAM Neural Networks with Time Delays by the Quadratic Analysis Approach," Mathematics, MDPI, vol. 11(6), pages 1-21, March.

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