Adaptive Synchronization of a Class of Chaotic Neural Networks with Time-varying Delays and Uncertain Parameters
This paper is concerned with the asymptotic synchronization of a class of time-varying delayed chaotic neural networks with parameter uncertainties. Using the drive-response concept, in terms of a linear matrix inequality (LMI) and the Lyapunov stability theory, two sufficient conditions for global asymptotic synchronization of uncertain chaotic delayed neural networks are derived under the differentiable and non-differentiable conditions of time-varying delays respectively, which also present a procedure to construct synchronization controllers. Under the non-differentiable condition of time-varying delays, the sufficient condition generalizes and further improves those in the earlier publications. The examples are given to demonstrate the effectiveness of the present method.
Chaotic neural networks Adaptive synchronization parameter uncertainties and Linear matrix inequality
Aiping Li Dongsheng Yang Zhengdong Yu Rencai Sun Qingqi Zhao
School of Information Science and Engineering Northeastern University Shenyang, China China Airport Construction Group Corporation of CAAC, Shenyang, China Liaoning Electric Power Co.,Ltd, Shenyang, China
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
2509-2514
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）