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

M. Hymavathi, Tarek F. Ibrahim, M. Syed Ali, Gani Stamov, Ivanka Stamova, B. A. Younis, Khalid I. Osman

2022Mathematics13 citationsDOIOpen Access PDF

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.

Topics & Concepts

Synchronization (alternating current)Reaction–diffusion systemArtificial neural networkControl theory (sociology)Constant (computer programming)Stability (learning theory)Fractional calculusDiffusionOrder (exchange)Computer scienceScheme (mathematics)Control (management)MathematicsApplied mathematicsTopology (electrical circuits)Mathematical analysisArtificial intelligencePhysicsMachine learningFinanceCombinatoricsEconomicsThermodynamicsProgramming languageNeural Networks Stability and Synchronizationstochastic dynamics and bifurcationNonlinear Dynamics and Pattern Formation