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.
Author: | Stephan BialonskiORCiD, Klaus Lehnertz |
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DOI: | https://doi.org/10.1142/9789814525350_0010 |
ISBN: | 978-981-4525-36-7 |
Parent Title (English): | Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction |
Document Type: | Part of a Book |
Language: | English |
Year of Completion: | 2013 |
Date of the Publication (Server): | 2018/10/09 |
First Page: | 132 |
Last Page: | 147 |
Link: | https://doi.org/10.1142/9789814525350_0010 |
Zugriffsart: | bezahl |
Institutes: | FH Aachen / Fachbereich Medizintechnik und Technomathematik |
collections: | Verlag / World Scientific |