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20092026
most citedComplex network approaches to nonlinear time series analysis

648 citations · 6.9k across the 60 of their papers we have counts for

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13 papers · 1 filter

physics.data-an2025★ 648 cited

Complex network approaches to nonlinear time series analysis

Yong Zou, Reik V. Donner, Norbert Marwan +2

In the last decade, there has been a growing body of literature addressing the utilization of complex network methods for the characterization of dynamical systems based on time se…

physics.data-an2021

Estimating nonlinear stability from time series data

Adrian van Kan, Jannes Jegminat, Jonathan Donges

Basin stability (BS) is a measure of nonlinear stability in multi-stable dynamical systems. BS has previously been estimated using Monte-Carlo simulations, which requires the expli…

physics.data-an2017★ 48 cited

Mapping and discrimination of networks in the complexity-entropy plane

Marc Wiedermann, Jonathan F. Donges, Jürgen Kurths +1

Complex networks are usually characterized in terms of their topological, spatial, or information-theoretic properties and combinations of the associated metrics are used to discri…

physics.data-an2016★ 53 cited

A climate network-based index to discriminate different types of El Niño and La Niña

Marc Wiedermann, Alexander Radebach, Jonathan F. Donges +2

El Niño exhibits distinct Eastern Pacific (EP) and Central Pacific (CP) types which are commonly, but not always consistently, distinguished from each other by different signatures…

physics.data-an2015★ 134 cited

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

Jonathan F. Donges, Jobst Heitzig, Boyan Beronov +9

We introduce the \texttt{pyunicorn} (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of dat…

physics.data-an2013★ 99 cited

Disentangling different types of El Niño episodes by evolving climate network analysis

Alexander Radebach, Reik V. Donner, Jakob Runge +2

Complex network theory provides a powerful toolbox for studying the structure of statistical interrelationships between multiple time series in various scientific disciplines. In t…