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From time series to complex networks: an overview

  • The network approach towards the analysis of the dynamics of complex systems has been successfully applied in a multitude of studies in the neurosciences and has yielded fascinating insights. With this approach, a complex system is considered to be composed of different constituents which interact with each other. Interaction structures can be compactly represented in interaction networks. In this contribution, we present a brief overview about how interaction networks are derived from multivariate time series, about basic network characteristics, and about challenges associated with this analysis approach.

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Metadaten
Verfasserangaben:Stephan BialonskiORCiD, Klaus Lehnertz
DOI:https://doi.org/10.1142/9789814525350_0010
ISBN:978-981-4525-36-7
Titel des übergeordneten Werkes (Englisch):Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction
Dokumentart:Teil eines Buches (Kapitel)
Sprache:Englisch
Erscheinungsjahr:2013
Datum der Publikation (Server):09.10.2018
Erste Seite:132
Letzte Seite:147
Link:https://doi.org/10.1142/9789814525350_0010
Zugriffsart:bezahl
Fachbereiche und Einrichtungen:FH Aachen / Fachbereich Medizintechnik und Technomathematik
collections:Verlag / World Scientific