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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

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, 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, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jnlamp:v:2022:y:2022:i:1:n:4227067
    DOI: 10.1155/2022/4227067
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    References listed on IDEAS

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