Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Robust adaptive synchronization of chaotic neural networks by slide technique|
|Citation:||Chinese Physics B, 2008; 17(2):520-528|
|School/Discipline:||School of Mathematical Sciences|
|Lou Xu-Yang and Cui Bao-Tong|
|Abstract:||In this paper, we focus on the robust adaptive synchronization between two coupled chaotic neural networks with all the parameters unknown and time-varying delay. In order to increase the robustness of the two coupled neural networks, the key idea is that a sliding-mode-type controller is employed. Moreover, without the estimate values of the network unknown parameters taken as an updating object, a new updating object is introduced in the constructing of controller. Using the proposed controller, without any requirements for the boundedness, monotonicity and differentiability of activation functions, and symmetry of connections, the two coupled chaotic neural networks can achieve global robust synchronization no matter what their initial states are. Finally, the numerical simulation validates the effectiveness and feasibility of the proposed technique.|
|Keywords:||robust adaptive synchronization; slide technique; chaotic neural networks; time-varying delay|
|Appears in Collections:||Mathematical Sciences publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.