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 |
|---|---|
| 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 |
