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Finite-Time Synchronization of Fractional-Order Complex-Valued Cohen-Grossberg Neural Networks with Mixed Time Delays and State-Dependent Switching

Author

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  • Xiaoxia Li
  • Yingzi Cao
  • Chi Zheng
  • Zhixin Feng
  • Guizhi Xu
  • Zine El Abiddine Fellah

Abstract

This paper discussed the finite-time synchronization of fractional-order complex-valued Cohen-Grossberg neural networks (FCVCGNNs), which contain mixed time delays and state-dependent switching that make the model more comprehensive. Different from other methods, we use a method of nonseparating real and imaginary parts to get our conclusions. By applying fractional-order inequalities and the Lyapunov function, effective controllers with suitable conditions are derived. Additionally, the maximum time for the drive-response system to reach synchronization is also given. Finally, numerical examples are designed to illustrate the effectiveness of our obtained theoretical results.

Suggested Citation

  • Xiaoxia Li & Yingzi Cao & Chi Zheng & Zhixin Feng & Guizhi Xu & Zine El Abiddine Fellah, 2022. "Finite-Time Synchronization of Fractional-Order Complex-Valued Cohen-Grossberg Neural Networks with Mixed Time Delays and State-Dependent Switching," Advances in Mathematical Physics, Hindawi, vol. 2022, pages 1-23, May.
    • Handle: RePEc:hin:jnlamp:4227067
    DOI: 10.1155/2022/4227067
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