Exponential synchronization for delayed chaotic neural networks with nonlinear hybrid coupling

This paper deals with global exponential synchronization in arrays of coupled delayed chaotic neural networks with nonlinear hybrid coupling. Through constructing one novel Lyapunov–Krasovskii functional, two novel synchronization criteria are presented in terms of linear matrix inequalities (LMIs) based on reciprocal convex technique, and these conditions are heavily dependent on the bounds of both time-delay and its derivative. Through employing LMI in Matlab Toolbox and adjusting some matrix parameters in the derived results, the design and applications of the generalized networks can be realized, which shows that our methods can improve some reported methods. The efficiency and applicability of the proposed methods can be demonstrated by three numerical examples with simulations.