A class of fast fixed-time synchronization control for the delayed neural network. Issue 1 (January 2018)

• Record Type: Journal Article
• Authors: Xu, Yuhua; Meng, Defeng; Xie, Chengrong; You, Guoqiao; Zhou, Wuneng
• Is Part Of: Journal of the Franklin Institute. Volume 355:Issue 1(2018)
• Page Start: 164
• Page End: 176
• Publication Date: 2018-01
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2017.11.006
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: This paper deals with the synchronization control of a class of delayed neural networks using a fast fixed-time control theory. By employing Lyapunov stability theory, a novel sufficient criterion is derived such that two neural networks can be synchronized within a fixed-time. Compared with some existing results, the proposed controller can render two neural networks faster synchronized. A numerical example is given to demonstrate the effectiveness of the criterion.