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Confidence bounds of recurrence-based complexity measures

  • In the recent past, recurrence quantification analysis (RQA) has gained an increasing interest in various research areas. The complexity measures the RQA provides have been useful in describing and analysing a broad range of data. It is known to be rather robust to noise and nonstationarities. Yet, one key question in empirical research concerns the confidence bounds of measured data. In the present Letter we suggest a method for estimating the confidence bounds of recurrence-based complexity measures. We study the applicability of the suggested method with model and real- life data.

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Metadaten
Author:Stefan Schinkel, Norbert Marwan, Olaf Dimigen, Jürgen KurthsORCiDGND
URL:http://www.sciencedirect.com/science/journal/03759601
DOI:https://doi.org/10.1016/j.physleta.2009.04.045
ISSN:0375-9601
Document Type:Article
Language:English
Year of first Publication:2009
Year of Completion:2009
Release Date:2017/03/25
Source:Physics letters A. - ISSN 0375-9601. - 373 (2009), 26, S. 2245 - 2250
Organizational units:Zentrale und wissenschaftliche Einrichtungen / Interdisziplinäres Zentrum für Dynamik komplexer Systeme
Peer Review:Referiert