Exponential synchronization of Cohen–Grossberg neural networks via periodically intermittent control

In this paper, a class of Cohen–Grossberg neural networks with time-varying delays are studied by designing a periodically intermittent controller. Some novel and effective exponential synchronization criteria are derived by applying some analysis techniques. These results generalize a few previous known results and remove some restrictions on control width and time-delays. Finally, a chaotic Cohen–Grossberg neural network is represented to show the effectiveness and feasibility of our results.