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  Nonlinear dynamics, synchronization and networks: Dedicated to Jürgen Kurths' 70th birthday

Ghosh, D., Marwan, N., Small, M., Kiss, I. Z., Zhou, C., Heitzig, J., Koseska, A., Ji, P. (Eds.) (2023): Nonlinear dynamics, synchronization and networks: Dedicated to Jürgen Kurths' 70th birthday [Special Issue]. - Chaos, 33, 8.

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

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 Abstract: This focus issue covers the recent developments in the broad areas of nonlinear dynamics, synchronization and emergent behavior in dynamical networks. This issue targets current progress on issues such as time series analysis, data-driven modeling from real data such as climate, brain, and social dynamics. Prediction or detecting an early warning signal of extreme climate conditions, epileptic seizures and other catastrophic conditions, are the most important tasks from real or experimental data. Exploring the machine-based learning of real data for the purpose of modeling and prediction is an emerging area. Tipping in a single element or in a network is an emerging direction for future research for the purpose of understanding and prediction. Recent progress of research on deriving a network from data available from biological, engineering and social systems is also covered.

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Language(s): eng - English
 Dates: 2023-082023-08
 Publication Status: Finally published
 Pages: -
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 Rev. Type: -
 Identifiers: Organisational keyword: RD4 - Complexity Science
PIKDOMAIN: RD4 - Complexity Science
 Degree: -

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Title: Chaos
Source Genre: Journal
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Pages: - Volume / Issue: 33 (8) Sequence Number: - Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808