| Title |
Event-based exponential synchronization of complex networks
|
|---|---|
| Published in |
Cognitive Neurodynamics, June 2016
|
| DOI | 10.1007/s11571-016-9391-3 |
| Pubmed ID | |
| Authors |
Bo Zhou, Xiaofeng Liao, Tingwen Huang |
| Abstract |
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. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Netherlands | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 29% |
| Professor > Associate Professor | 1 | 14% |
| Researcher | 1 | 14% |
| Lecturer | 1 | 14% |
| Unknown | 2 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 2 | 29% |
| Neuroscience | 2 | 29% |
| Economics, Econometrics and Finance | 1 | 14% |
| Unknown | 2 | 29% |
Attention Score in Context
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#19,630,735
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Outputs from Cognitive Neurodynamics
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Outputs of similar age from Cognitive Neurodynamics
#1
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