p-th exponential synchronization of Cohen-Grossberg neural network with mixed time-varying delays and unknown parameters using impulsive control method

In this paper, we investigate the p-th exponential synchronization of Cohen-Grossberg neural network with mixed time-varying delays and unknown parameters by general impulsive controller. Based on impulsive and different time-varying delays, it makes the neural network model very general and practical. A nonlinear impulsive controller is designed to guarantee that the response system can be synchronized with a drive system by utilizing Lyapunov stability theory and parameter identification. Our synchronization criteria are easily verified and do not need to solve any linear matrix inequality. These results generalize a few previous known results and remove some restrictions on the neural networks. Finally, a numerical example and its simulations are provided to demonstrate the effectiveness and advantage of the theoretical results.