Synchronization and Parameter Identification for a Class of Chaotic Neural Networks with Time-Varying Delays via Adaptive Control

The paper aims to present a synchronization and parameter identification scheme for a class of time-varying neural networks. By combining the adaptive control method and the Razumikhin-type Theorem, a novel delay-independent and decentralized linear-feedback control with appropriate updated law is designed to achieve the synchronization and parameter identification .The updating law of parameters can be directly constructed. Hopfield neural networks with time-varying delays are given to show the effectiveness of the presented synchronization scheme.