Title :
A Synchronization Approach of Delay Chaotic Neural Networks
Author :
Qiao, Zong-min ; Cheng, Jia-xing ; Song, Jie
Abstract :
In this paper, global synchronization is discussed for chaotic neural networks time-varying delay. An effective synchronization law in matrix inequality form has been derived for time-varying delayed chaotic neural networks based on Lyapunov method and LMI technique. The advantage of the proposed approach can be performed efficiently via numerical algorithms such as the interior-point algorithms for solving LMIs. Moreover, one can get two less conservative controller gain matrixes simultaneous by solving a LMI. Numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.
Keywords :
Lyapunov matrix equations; chaos; delay systems; linear matrix inequalities; neurocontrollers; nonlinear control systems; synchronisation; time-varying systems; Lyapunov method; chaotic neural networks time-varying delay system; linear matrix inequality; synchronization approach; Chaos; Cybernetics; Delay effects; Linear matrix inequalities; Machine learning; Neural networks; Neurons; Numerical simulation; Signal processing algorithms; Sufficient conditions; Chaotic system; Delay; Synchronization;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370165