Title :
New conditions for synchronization of a class of chaotic neural networks
Author :
Zhao, Zhe ; Wu, Xueli ; Ding, Xue
Author_Institution :
Coll. of Electron. Eng. & Inf., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Abstract :
Chaos control and synchronization in the chaotic neural networks is discussed in this paper. Based on the stability theory of a cascade-connected system, adaptive control laws are presented to achieve chaos synchronization. The sliding model synchronization controller designed to satisfy the external disturbance vector with unknown upper bound. The advantage of the proposed controllers is that they are linear and have lower dimensions than that of the states. Simulation results for chaotic systems are provided to illustrate the effectiveness of the proposed scheme.
Keywords :
adaptive control; chaotic communication; neural nets; stability; synchronisation; adaptive control; cascade connected system; chaos control; chaotic neural network; stability theory; synchronization controller; Artificial neural networks; Asymptotic stability; Chaotic communication; Delay; Lyapunov method; Synchronization; Chaotic neural networks; Sliding model control; Synchronization; Time delay;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5584874
