Title :
Globally Exponential Synchronization and Parameter Regulation of Chaotic Neural Networks with Time-Varying Delays via Adaptive Control
Author :
Wang, Zhongsheng ; Xiang, Dan ; Yan, Nin
Author_Institution :
Coll. of Autom., Guangdong Polytech. Normal Univ., Guangzhou
Abstract :
The paper aims to present a globally exponential synchronization and parameter regulation scheme for a class of time-varying neural networks, which covers the Hopfield neural networks and cellular neural networks. By combining the adaptive control method and the Razumikhin-type theorem, a delay-independent and decentralized linear-feedback control with appropriate updated law is designed to achieve the globally exponential synchronization. The regulating law of parameters can be directly constructed. Hopfield neural networks with time-varying delays is given to show the effectiveness of the presented synchronization scheme.
Keywords :
Hopfield neural nets; adaptive control; cellular neural nets; decentralised control; delays; feedback; synchronisation; time-varying systems; Hopfield neural networks; Razumikhin-type theorem; adaptive control; cellular neural networks; chaotic neural networks; decentralized linear-feedback control; globally exponential synchronization; parameter regulation; time-varying delays; time-varying neural networks; Adaptive control; Cellular neural networks; Chaos; Chaotic communication; Computer networks; Delay effects; Delay lines; Hopfield neural networks; Neural networks; Neurons; Adaptive control; Chaotic Neural Networks; Globally Exponential Synchronization; Parameter Regulation; Stability Theorem; Time-Varying Delays;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.32
