Correlation Dimension of Complex Networks

被引：73

作者：

Lacasa, Lucas ^{[1
]}

Gomez-Gardenes, Jesus ^{[2
,3
]}

机构：

[1] Univ Politecn Madrid, ETSI Aeronaut, Dept Matemat Aplicada & Estadist, E-28040 Madrid, Spain

[2] Univ Zaragoza, Dept Fis Mat Condensada, E-50009 Zaragoza, Spain

[3] Univ Zaragoza, Inst Biocomputat & Phys Complex Syst BIFI, E-50009 Zaragoza, Spain

来源：

PHYSICAL REVIEW LETTERS | 2013年 / 110卷 / 16期

关键词：

SIMILARITY;

D O I：

10.1103/PhysRevLett.110.168703

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers. DOI: 10.1103/PhysRevLett.110.168703

引用

页数：5