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Network coherence in the web graphs
DOI:10.1016/j.cnsns.2015.03.011.png)
摘要
En 中文
Network coherence is used to characterize the consensus dynamics with additive stochastic disturbances and can be described by Laplacian spectrum. In this paper, we mainly obtain the scalings of network coherence in the web graphs with a special feature that its fractal dimension is infinite. We then investigate the relationship between the scalings and fractal dimension. Based on the structures of web graphs, we obtain the relationships for Laplacian matrix and Laplacian eigenvalues between web graphs and their corresponding equilateral polygons. We also obtain analytical expressions for the sum of the reciprocals and square reciprocals of all nonzero Laplacian eigenvalues. Finally we calculate first and second order coherence and see that the scalings of network coherence with network size N are N and N-3, which shows that the scalings are not related to the fractal dimension of web graphs. In addition, the scalings of network coherence in web graphs are larger than those performed on some fractal networks. (C) 2015 Elsevier B.V. All rights reserved.
Keyword:
Network coherence
Laplacian spectrum
Web graphs
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期刊
IF:
3.8
论文数:
9.3K
被引数:
1.8W
机构
引用论文
Second-order consensus in multi-agent dynamical systems with sampled position data具有采样位置数据的多智能体动力学系统中的二阶一致性
AUTOMATICA
IF5.9

