Detection of Causal Relations in Time Series Affected by Noise in Tokamaks Using Geodesic Distance on Gaussian Manifolds

Detection of Causal Relations in Time Series Affected by Noise in Tokamaks Using Geodesic Distance on Gaussian Manifolds

Abstract: Modern experiments in Magnetic Confinement Nuclear Fusion can produce Gigabytes of data, mainly in form of time series. The acquired signals, composing massive databases, are typically affected by significant levels of noise. The interpretation of the time series can therefore become quite...

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Hlavní autoři: Andrea Murari, Teddy Craciunescu, Emmanuele Peluso, Michela Gelfusa, JET Contributors
Médium: Článek
Jazyk:English
Vydáno: MDPI AG 2017-10-01
Edice:Entropy
Témata:
information geometry
geodesic distance on Gaussian manifolds
recurrence plots
complex networks
ELMs
sawteeth
pacing experiments
Tokamaks
entropy
On-line přístup:https://www.mdpi.com/1099-4300/19/10/569

Internet

https://www.mdpi.com/1099-4300/19/10/569

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