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Global exponential synchronization of multiple coupled inertial memristive neural networks with time-varying delay
Zhenyuan Guo1, Shuqing Gong1, Shaofu Yang2
1College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, China.
Abstract:
In this paper, global exponential synchronization of multiple coupled inertial memristive neural networks with time-varying delay is investigated. First, by choosing suitable variable substitution, the inertial memristive neural networks are transformed into first-order differential equations. Next, a novel coupling scheme with linear diffusive term and discontinuous sign function term depending on the first order derivative of state variables is introduced. Based on this coupling scheme, several sufficient conditions for global exponential synchronization of multiple inertial memristive neural networks are derived by using Lyapunov stability theory and some inequality techniques. Finally, several numerical examples are presented to substantiate the effectiveness of the theoretical results.
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