Data analysis techniques: Difference between revisions
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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. | 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. | ||
* [[Function parametrization]] | * [[Function parametrization]] | ||
* Bayesian analysis | * Bayesian data analysis <ref>[http://link.aip.org/link/?RSINAK/75/4237/1 R. Fischer, A. Dinklage, ''Integrated data analysis of fusion diagnostics by means of the Bayesian probability theory'', Rev. Sci. Instrum. '''75''' (2004) 4237]</ref><ref>[http://dx.doi.org/10.1109/WISP.2007.4447579 J. Svensson, A. Werner, ''Large Scale Bayesian Data Analysis for Nuclear Fusion Experiments'', IEEE International Symposium on Intelligent Signal Processing (2007) 1]</ref> | ||
== References == | |||
<references /> | |||
Revision as of 15:20, 9 February 2010
This page collects information on data analysis techniques used in fusion research.
Temporal analysis
Linear analysis
- Correlation
- Fourier analysis
- Wavelet analysis
- Conditional analysis
- Probability distributions
- Rescaled range or Hurst analysis; Structure functions
Non-linear analysis
- Bicoherence analysis
- Chaos analysis (attractors, fractional dimensions)
- Hilbert-Huang transform
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.
- Function parametrization
- Bayesian data analysis [1][2]
References
- ↑ R. Fischer, A. Dinklage, Integrated data analysis of fusion diagnostics by means of the Bayesian probability theory, Rev. Sci. Instrum. 75 (2004) 4237
- ↑ J. Svensson, A. Werner, Large Scale Bayesian Data Analysis for Nuclear Fusion Experiments, IEEE International Symposium on Intelligent Signal Processing (2007) 1