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  Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis

Lekscha, J., Donner, R. V. (2020): Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis. - Nonlinear Processes in Geophysics, 27, 2, 261-275.
https://doi.org/10.5194/npg-27-261-2020

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_23949 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_23949_4
Genre: Journal Article

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 Creators:
Lekscha, Jaqueline1, Author              
Donner, Reik V.1, Author              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Dates: 2020-03-262020
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.5194/npg-27-261-2020
PIKDOMAIN: RD4 - Complexity Science
eDoc: 8993
Working Group: Development of advanced time series analysis techniques
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Title: Nonlinear Processes in Geophysics
Source Genre: Journal, SCI, Scopus, p3, oa
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Pages: - Volume / Issue: 27 (2) Sequence Number: - Start / End Page: 261 - 275 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals364
Publisher: Copernicus