Synchronization of unknown chaotic delayed competitive neural networks with different time scales based on adaptive control and parameter identification

In this paper, we investigate the synchronization problems of delayed competitive neural networks with different time scales and unknown parameters. A simple and robust adaptive controller is designed such that the response system can be synchronized with a drive system with unknown parameters by utilizing Lyapunov stability theory and parameter identification. Our synchronization criteria are easily verified and do not need to solve any linear matrix inequality. This research also demonstrates the effectiveness of application in secure communication. Numerical simulations are carried out to illustrate the main results.