Finite-time parameter identification and adaptive synchronization between two chaotic neural networks

This work presents an approach for finite-time synchronization to identify all the unknown parameters for two coupled neural networks with time delay. Based on the finite-time stability theory, an effective feedback control with an updated law is designed to finite-time synchronization between two chaotic neural networks. Since finite-time topology identification means the suboptimum in the identification time, the results of this paper are important. Finally, an illustrative example is given to show the effectiveness of the main results.