Journal article
Persistent homology of time-dependent functional networks constructed from coupled time series
- Abstract:
-
We use topological data analysis to study “functional networks” that we construct from time-series data from both experimental and synthetic sources. We use persistent homology with a weight rank clique filtration to gain insights into these functional networks, and we use persistence landscapes to interpret our results. Our first example uses time-series output from networks of coupled Kuramoto oscillators. Our second example consists of biological data in the form of functional magnetic res...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Authors
Funding
+ Engineering and Physical Sciences Research Council
More from this funder
Funding agency for:
Stolz, B
Grant:
EP/G037280/1
+ Engineering and Physical Sciences Research Council
More from this funder
Funding agency for:
Harrington, H
Grant:
EP/K041096/1
Bibliographic Details
- Publisher:
- AIP Publishing Publisher's website
- Journal:
- Chaos Journal website
- Volume:
- 27
- Issue:
- 4
- Article number:
- 047410
- Publication date:
- 2017-04-28
- Acceptance date:
- 2017-01-04
- DOI:
- EISSN:
-
1089-7682
- ISSN:
-
1054-1500
- Source identifiers:
-
668038
Item Description
- Keywords:
- Pubs id:
-
pubs:668038
- UUID:
-
uuid:4b711003-f431-44be-b919-d95a02776c38
- Local pid:
- pubs:668038
- Deposit date:
- 2017-01-04
Terms of use
- Copyright holder:
- Stolz et al
- Copyright date:
- 2017
- Notes:
- Published by AIP Publishing. [http://dx.doi.org/10.1063/1.4978997]
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