Data analysis techniques: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
No edit summary |
||
| Line 10: | Line 10: | ||
* Conditional analysis | * Conditional analysis | ||
* Probability distributions | * Probability distributions | ||
=== Non-linear analysis === | === Non-linear analysis === | ||
* [[:Wikipedia:Bicoherence|Bicoherence]] | * [[:Wikipedia:Bicoherence|Bicoherence]], bispectrum | ||
* Chaos analysis ([[:Wikipedia:Attractor|Strange attractor]], [[:Wikipedia:Fractal dimension|Fractal dimension]], [[:Wikipedia:Mutual information|Mutual information]]) | * Chaos analysis ([[:Wikipedia:Attractor|Strange attractor]], [[:Wikipedia:Fractal dimension|Fractal dimension]], [[:Wikipedia:Mutual information|Mutual information]], [[:Wikipedia:Lyapunov exponent|Lyapunov exponent]]) | ||
* [[:Wikipedia:Hilbert-Huang transform|Hilbert-Huang transform]] | * [[:Wikipedia:Hilbert-Huang transform|Hilbert-Huang transform]] | ||
=== Self-similarity === | |||
* [[:Wikipedia:Rescaled range|Rescaled range]] or Hurst analysis; Structure functions | |||
* Waiting times, quiet times <ref>[ | |||
http://link.aps.org/doi/10.1103/PhysRevE.66.036124 R. Sánchez et a., ''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> | |||
== Spatial analysis == | == Spatial analysis == | ||
| Line 43: | Line 48: | ||
[[Error propagation]] | [[Error propagation]] | ||
== References == | |||
<references /> | |||
Revision as of 21:36, 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.
See also
References
- ↑ [ http://link.aps.org/doi/10.1103/PhysRevE.66.036124 R. Sánchez et a., 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)]