Fixed-deviation stabilization and synchronization for delayed fractional-order complex-valued neural networks

Bingrui Zhang; Jin-E Zhang; Bingrui Zhang; Jin-E Zhang

doi:10.3934/mbe.2023449

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 6: 10244-10263. doi: 10.3934/mbe.2023449

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Fixed-deviation stabilization and synchronization for delayed fractional-order complex-valued neural networks

Bingrui Zhang ,
Jin-E Zhang ^,

School of Mathematics and Statistics, Hubei Normal University, Huangshi 435002, China
Academic editor: Xiaodi Li

Received: 21 February 2023 Revised: 20 March 2023 Accepted: 23 March 2023 Published: 30 March 2023

In this paper, we study fixed-deviation stabilization and synchronization for fractional-order complex-valued neural networks with delays. By applying fractional calculus and fixed-deviation stability theory, sufficient conditions are given to ensure the fixed-deviation stabilization and synchronization for fractional-order complex-valued neural networks under the linear discontinuous controller. Finally, two simulation examples are presented to show the validity of theoretical results.
- fractional-order complex-valued neural networks,
- time delays,
- fixed-deviation dynamics,
- discontinuous control
Citation: Bingrui Zhang, Jin-E Zhang. Fixed-deviation stabilization and synchronization for delayed fractional-order complex-valued neural networks[J]. Mathematical Biosciences and Engineering, 2023, 20(6): 10244-10263. doi: 10.3934/mbe.2023449

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Abstract

In this paper, we study fixed-deviation stabilization and synchronization for fractional-order complex-valued neural networks with delays. By applying fractional calculus and fixed-deviation stability theory, sufficient conditions are given to ensure the fixed-deviation stabilization and synchronization for fractional-order complex-valued neural networks under the linear discontinuous controller. Finally, two simulation examples are presented to show the validity of theoretical results.

References

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