Exponential synchronization of stochastic Cohen–Grossberg neural networks with mixed time-varying delays and reaction–diffusion via periodically intermittent control

The issue of exponential synchronization for Cohen–Grossberg neural networks with mixed time-varying delays, stochastic noise disturbance and reaction–diffusion effects is investigated. An approach combining Lyapunov stability theory with stochastic analysis approaches and periodically intermittent control is taken to investigate this problem. The proposed criterion for exponential synchronization generalizes and improves those reported recently in the literature. This paper also presents an illustrative example and uses simulated results of this example to show the feasibility and effectiveness of the proposed scheme.

► The synchronization of reaction diffusion Cohen–Grossberg neural networks is studied. ► An intermittent controller to guarantee the synchronization is obtained. ► Numerical simulations are given to show the effectiveness of theoretical results.