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From fuzzy recurrence plots to scalable recurrence networks of time series
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. (Medical Informatics)ORCID iD: 0000-0002-4255-5130
2017 (English)In: Europhysics letters, ISSN 0295-5075, E-ISSN 1286-4854, Vol. 118, 20003Article in journal (Refereed) Published
Abstract [en]

Recurrence networks, which are derived from recurrence plots of nonlinear time series, enable the extraction of hidden features of complex dynamical systems. Because fuzzy recurrence plots are represented as grayscale images, this paper presents a variety of texture features that can be extracted from fuzzy recurrence plots. Based on the notion of fuzzy recurrence plots, defuzzified, undirected, and unweighted recurrence networks are introduced. Network measures can be computed for defuzzified recurrence networks that are scalable to meet the demand for the network-based analysis of big data.

Place, publisher, year, edition, pages
Institute of Physics (IOP), 2017. Vol. 118, 20003
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URN: urn:nbn:se:liu:diva-138502DOI: 10.1209/0295-5075/118/20003OAI: oai:DiVA.org:liu-138502DiVA: diva2:1110900
Available from: 2017-06-16 Created: 2017-06-16 Last updated: 2017-09-08

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The full text will be freely available from 2018-06-21 15:16
Available from 2018-06-21 15:16

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Pham, Tuan
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CiteExportLink to record
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Citation style
  • apa
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  • asciidoc
  • rtf