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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 23/2021

24.08.2021 | Original Article

Exponential synchronization of fractional-order multilayer coupled neural networks with reaction-diffusion terms via intermittent control

verfasst von: Yao Xu, Fu Sun, Wenxue Li

Erschienen in: Neural Computing and Applications | Ausgabe 23/2021

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Abstract

In this paper, the issue of exponential synchronization of fractional-order multilayer coupled neural networks with reaction-diffusion terms is investigated by using periodically intermittent control. It deserves to mention that spatial diffusions, multilayer interactions and fractional dynamics are introduced to coupled neural networks at the same time. A novel fractional-order differential inequality is established on the basis of Caputo partial fractional operator. Moreover, to realize exponential synchronization of the underlying neural networks, some sufficient conditions are presented with the help of Lyapunov method and graph theory. Theoretical results show that the exponential convergence rate is dependent on the control gain and the order of fractional derivative. Finally, an illustrative numerical example is provided to further verify the feasibility and effectiveness of our results.
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Metadaten
Titel
Exponential synchronization of fractional-order multilayer coupled neural networks with reaction-diffusion terms via intermittent control
verfasst von
Yao Xu
Fu Sun
Wenxue Li
Publikationsdatum
24.08.2021
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 23/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-021-06214-0

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