Statistical Self-Similar Properties of Complex Networks

Details Statistical Self-Similar Properties of Complex Networks Statistical Self-Similar Properties of Complex Networks

2006-05-23

arxiv.org/abs/physics/0605205v1

Physics

Physics and Society

11 pages, 4 figures

Scientific paper

10.1103/PhysRevE.73.066102

It has been shown that many complex networks shared distinctive features, which differ in many ways from the random and the regular networks. Although these features capture important characteristics of complex networks, their applicability depends on the type of networks. To unravel ubiquitous characteristics that complex networks may have in common, we adopt the clustering coefficient as the probability measure, and present a systematic analysis of various types of complex networks from the perspective of statistical self-similarity. We find that the probability distribution of the clustering coefficient is best characterized by the multifractal; moreover, the support of the measure had a fractal dimension. These two features enable us to describe complex networks in a unified way; at the same time, offer unforeseen possibilities to comprehend complex networks.

Affiliated with

Also associated with

No associations

Rating

Statistical Self-Similar Properties of Complex Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Statistical Self-Similar Properties of Complex Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Statistical Self-Similar Properties of Complex Networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-72410