Cognitive Neurodynamics

, Volume 10, Issue 5, pp 423–436 | Cite as

Event-based exponential synchronization of complex networks

  • Bo Zhou
  • Xiaofeng Liao
  • Tingwen Huang
Research Article


In this paper, we consider exponential synchronization of complex networks. The information diffusions between nodes are driven by properly defined events. By employing the M-matrix theory, algebraic graph theory and the Lyapunov method, two kinds of distributed event-triggering laws are designed, which avoid continuous communications between nodes. Then, several criteria that ensure the event-based exponential synchronization are presented, and the exponential convergence rates are obtained as well. Furthermore, we prove that Zeno behavior of the event-triggering laws can be excluded before synchronization being achieved, that is, the lower bounds of inter-event times are strictly positive. Finally, a simulation example is provided to illustrate the effectiveness of theoretical analysis.


Event-triggered synchronization Complex networks Strongly connected network Directed spanning tree Convergence rate 



This work was supported in part by the National Natural Science Foundation of China under Grant 61273021, 61503308, in part by the Natural Science Foundation Project of Chongqing under grant cstc2013jjB40008, in part by the Research Fund of Preferential Development Domain for the Doctoral Program of Ministry of Education of China under Grant 201101911130005, in part by the fundamental research funds for the central universities under Grant XDJK2014D029. This work is also supported in part by NPRP Grant #4-1162-1-181 from the Qatar National Research Fund (a member of Qatar Foundation).


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.College of Electronic and Information EngineeringSouthwest UniversityChongqingChina
  2. 2.Texas A&M University at QatarDohaQatar

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