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

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.

Automated summary

This paper investigates the issue of exponential synchronization of fractional-order multilayer coupled neural networks with reaction-diffusion terms using periodically intermittent control. Theoretical results show that the exponential convergence rate depends on the control gain and the order of fractional derivative. An illustrative numerical example is provided to further verify the feasibility and effectiveness of the results.