Data analysis techniques: Difference between revisions
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* [[:Wikipedia:Rescaled range|Rescaled range]] or Hurst analysis; Structure functions | * [[:Wikipedia:Rescaled range|Rescaled range]] or Hurst analysis; Structure functions | ||
* Waiting times, quiet times <ref>[ | * Waiting times, quiet times <ref>[http://link.aps.org/doi/10.1103/PhysRevE.66.036124 R. Sánchez et al., ''Quiet-time statistics: A tool to probe the dynamics of self-organized-criticality systems from within the strong overlapping regime'', Phys. Rev. E '''66''', 036124 (2002)]</ref> | ||
http://link.aps.org/doi/10.1103/PhysRevE.66.036124 R. Sánchez et | |||
== Spatial analysis == | == Spatial analysis == | ||
Revision as of 21:37, 13 February 2010
This page collects information on data analysis techniques used in fusion research.
Temporal analysis
Linear analysis
Non-linear analysis
- Bicoherence, bispectrum
- Chaos analysis (Strange attractor, Fractal dimension, Mutual information, Lyapunov exponent)
- Hilbert-Huang transform
Self-similarity
- Rescaled range or Hurst analysis; Structure functions
- Waiting times, quiet times [1]
Spatial analysis
Most of the techniques listed under 'temporal analysis' can of course be applied to spatial data.
- Tomography (cf. TJ-II:Tomography)
Spatio-temporal analysis
Image analysis
- Twodimensional Fourier analysis
- Twodimensional wavelet analysis
- Event detection using thresholding
- Optical flow (for movies)
Integrated data analysis
The goal of integrated data analysis is to combine the information from a set of diagnostics providing complementary information in order to recover the best possible reconstruction of the actual state of the system subjected to measurement.