Advances in Mathematical Physics (Jan 2022)

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

  • Xiaoxia Li,
  • Yingzi Cao,
  • Chi Zheng,
  • Zhixin Feng,
  • Guizhi Xu

DOI
https://doi.org/10.1155/2022/4227067
Journal volume & issue
Vol. 2022

Abstract

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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.