Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/4844
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electronic and Information Engineering | - |
dc.creator | Zhang, J | - |
dc.creator | Small, M | - |
dc.date.accessioned | 2014-12-11T08:24:51Z | - |
dc.date.available | 2014-12-11T08:24:51Z | - |
dc.identifier.issn | 0031-9007 | - |
dc.identifier.uri | http://hdl.handle.net/10397/4844 | - |
dc.language.iso | en | en_US |
dc.publisher | American Physical Society | en_US |
dc.rights | Physical Review Letters © 2006 The American Physical Society. The Journal's web site is located at http://prl.aps.org/ | en_US |
dc.subject | Chaos theory | en_US |
dc.subject | Embedded systems | en_US |
dc.subject | Large scale systems | en_US |
dc.subject | Spurious signal noise | en_US |
dc.subject | Statistical methods | en_US |
dc.subject | Time series analysis | en_US |
dc.subject | Topology | en_US |
dc.title | Complex network from pseudoperiodic time series : topology versus dynamics | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.description.otherinformation | Author name used in this publication: M. Small | en_US |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 4 | - |
dc.identifier.volume | 96 | - |
dc.identifier.issue | 23 | - |
dc.identifier.doi | 10.1103/PhysRevLett.96.238701 | - |
dcterms.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. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Physical review letters, 16 June 2006, v. 96, no. 23, 238701, p. 1-4 | - |
dcterms.isPartOf | Physical review letters | - |
dcterms.issued | 2006-06-14 | - |
dc.identifier.isi | WOS:000238315600062 | - |
dc.identifier.scopus | 2-s2.0-33745216051 | - |
dc.identifier.eissn | 1079-7114 | - |
dc.identifier.rosgroupid | r29831 | - |
dc.description.ros | 2005-2006 > Academic research: refereed > Publication in refereed journal | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Zhang_Complex_Network _Pseudoperiodic.pdf | 398.72 kB | Adobe PDF | View/Open |
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