Synchronization of Fractional-Order Neural Networks with Time Delays and Reaction-Diffusion Terms via Pinning Control

Date
2022-10-21
Authors
Hymavathi, M.
Ibrahim, Tarek F.
Ali, M. Syed
Stamov, Gani
Stamova, Ivanka
Younis, B. A.
Osman, Khalid I.
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Abstract

This paper introduces a novel synchronization scheme for fractional-order neural networks with time delays and reaction-diffusion terms via pinning control. We consider Caputo fractional derivatives, constant delays and distributed delays in our model. Based on the stability behavior, fractional inequalities and Lyapunov-type functions, several criteria are derived, which ensure the achievement of a synchronization for the drive-response systems. The obtained criteria are easy to test and are in the format of inequalities between the system parameters. Finally, numerical examples are presented to illustrate the results. The obtained criteria in this paper consider the effect of time delays as well as the reaction-diffusion terms, which generalize and improve some existing results.

Description
Keywords
synchronization, neural network models, fractional derivatives, time delays, reaction-diffusion terms, pinning control
Citation
Mathematics 10 (20): 3916 (2022)
Department
Mathematics