Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/5372
Title: Multiscale characterization of recurrence-based phase space networks constructed from time series
Authors: Xiang, R
Zhang, J
Xu, X
Small, M
Keywords: Complex networks
Time series
Issue Date: Mar-2012
Publisher: American Institute of Physics
Source: Chaos: an interdisciplinary journal of nonlinear science, Mar. 2012, v. 22, no. 1, 013107, p. 1-10 How to cite?
Journal: Chaos: an interdisciplinary journal of nonlinear science 
Abstract: Recently, a framework for analyzing time series by constructing an associated complex network has attracted significant research interest. One of the advantages of the complex network method for studying time series is that complex network theory provides a tool to describe either important nodes, or structures that exist in the networks, at different topological scale. This can then provide distinct information for time series of different dynamical systems. In this paper, we systematically investigate the recurrence-based phase space network of order k that has previously been used to specify different types of dynamics in terms of the motif ranking from a different perspective. Globally, we find that the network size scales with different scale exponents and the degree distribution follows a quasi-symmetric bell shape around the value of 2k with different values of degree variance from periodic to chaotic Rössler systems. Local network properties such as the vertex degree, the clustering coefficients and betweenness centrality are found to be sensitive to the local stability of the orbits and hence contain complementary information.
URI: http://hdl.handle.net/10397/5372
ISSN: 1054-1500 (print)
1089-7682 (online)
DOI: 10.1063/1.3673789
Rights: © 2012 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Ruoxi Xiang et al., Chaos: an interdisciplinary journal of nonlinear science 22, 013107 (2012) and may be found at http://link.aip.org/link/?cha/22/013107
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