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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2021 . Peer-reviewed
License: Springer TDM
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Recurrence Quantification Analysis: Theory and Applications

Authors: Giuseppe Orlando; Giovanna Zimatore; Alessandro Giuliani;

Recurrence Quantification Analysis: Theory and Applications

Abstract

Complex systems are characterized by deterministic laws (which often may be hidden) and randomness. A tool to analyse those systems is recurrence quantification analysis (RQA). RQA does not rely on any sort of assumption of stationarity and is not sensitive to singularities and transitions. It could be applied to both numeric and symbolic data, and it has a wide array of applications ranging from economics to biochemistry, physiology and physics. In Sect. 10.2, we introduce the reader to the recurrence plot, and in Sect. 10.3 to the recurrence quantification analysis. In Sect. 10.4, we exhibit specific examples of the application of RQA. This is of great importance because RQA can be adopted to derive an indicator of structural changes in a signal related to chaos.

Country
Italy
Keywords

RP, Time series, Chaos, RQA, Business cycles, Embedding

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
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