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.
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 |