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  Recent achievements in nonlinear dynamics, synchronization, and networks [Editorial]

Ghosh, D., Marwan, N., Small, M., Zhou, C., Heitzig, J., Koseska, A., Ji, P., Kiss, I. Z. (2024): Recent achievements in nonlinear dynamics, synchronization, and networks [Editorial]. - Chaos, 34, 10, 100401.
https://doi.org/10.1063/5.0236801

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 Creators:
Ghosh, Dibakar1, Author
Marwan, Norbert2, Author              
Small, Michael1, Author
Zhou, Changsong1, Author
Heitzig, Jobst2, Author              
Koseska, Aneta1, Author
Ji, Peng1, Author
Kiss, Istvan Z.1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: This Focus Issue covers recent developments in the broad areas of nonlinear dynamics, synchronization, and emergent behavior in dynamical networks. It targets current progress on issues such as time series analysis and data-driven modeling from real data such as climate, brain, and social dynamics. Predicting and detecting early warning signals of extreme climate conditions, epileptic seizures, or other catastrophic conditions are the primary tasks from real or experimental data. Exploring machine-based learning from real data for the purpose of modeling and prediction is an emerging area. Application of the evolutionary game theory in biological systems (eco-evolutionary game theory) is a developing direction for future research for the purpose of understanding the interactions between species. Recent progress of research on bifurcations, time series analysis, control, and time-delay systems is also discussed.

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Language(s): eng - English
 Dates: 2024-10-232024-10-23
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1063/5.0236801
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Organisational keyword: FutureLab - Game Theory & Networks of Interacting Agents
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Complex Networks
Model / method: Nonlinear Data Analysis
 Degree: -

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Title: Chaos
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 34 (10) Sequence Number: 100401 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: American Institute of Physics (AIP)