Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/4844
Title: Complex network from pseudoperiodic time series : topology versus dynamics
Authors: Zhang, J.
Small, Michael
Subjects: Chaos theory
Embedded systems
Large scale systems
Spurious signal noise
Statistical methods
Time series analysis
Topology
Issue Date: 14-Jun-2006
Publisher: American Physical Society
Source: Physical review letters, 16 June 2006, v. 96, no. 23, 238701, p. 1-4.
Abstract: We construct complex networks from pseudoperiodic time series, with each cycle represented by a single node in the network. We investigate the statistical properties of these networks for various time series and find that time series with different dynamics exhibit distinct topological structures. Specifically, noisy periodic signals correspond to random networks, and chaotic time series generate networks that exhibit small world and scale free features. We show that this distinction in topological structure results from the hierarchy of unstable periodic orbits embedded in the chaotic attractor. Standard measures of structure in complex networks can therefore be applied to distinguish different dynamic regimes in time series. Application to human electrocardiograms shows that such statistical properties are able to differentiate between the sinus rhythm cardiograms of healthy volunteers and those of coronary care patients.
Rights: Physical Review Letters © 2006 The American Physical Society. The Journal's web site is located at http://prl.aps.org/
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/4844
DOI: 10.1103/PhysRevLett.96.238701
ISSN: 0031-9007 (print)
1079-7114 (online)
Appears in Collections:EIE Journal/Magazine Articles

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