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

Urheber*innen

Ghosh,  Dibakar
External Organizations;

/persons/resource/Marwan

Marwan,  Norbert
Potsdam Institute for Climate Impact Research;

Small,  Michael
External Organizations;

Kiss,  Istvan Z.
External Organizations;

Zhou,  Changsong
External Organizations;

/persons/resource/heitzig

Heitzig,  Jobst
Potsdam Institute for Climate Impact Research;

Koseska,  Aneta
External Organizations;

Ji,  Peng
External Organizations;

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Zitation

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.


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_28708
Zusammenfassung
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.