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Exponential synchronization of complex dynamical networks with time-varying inner coupling via event-triggered communication.

Authors :
Dai, Hao
Chen, Weisheng
Jia, Jinping
Liu, Jiayun
Zhang, Zhengqiang
Source :
Neurocomputing. Jul2017, Vol. 245, p124-132. 9p.
Publication Year :
2017

Abstract

This paper investigates the problem of the exponential synchronization of complex dynamical networks with time-varying inner coupling via event-triggered communication. The network topology is assumed to have a spanning tree. A sufficient condition is derived to guarantee the exponential synchronization by employing the special Lyapunov stability analysis method, which by combining the difference and differential of the Lyapunov function rather than the single difference or differential. The main advantage of this paper is to avoid continuous communication between network nodes, which can decrease the number of information updates, reduce the network congestion and avoid the waste of network resources. Moreover, the Zeno behavior is excluded as well by the strictly positive sampling intervals. Finally, A simulation example is given to show the effectiveness of the proposed exponential synchronization criteria. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
245
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
122478537
Full Text :
https://doi.org/10.1016/j.neucom.2017.03.035