Data analysis techniques: Difference between revisions

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* Chaos analysis ([[:Wikipedia:Attractor|Strange attractor]], [[:Wikipedia:Fractal dimension|Fractal dimension]], [[:Wikipedia:Mutual information|Mutual information]], [[:Wikipedia:Lyapunov exponent|Lyapunov exponent]])
* 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]] <ref>N. Huang and S. Shen, ''Hilbert-Huang transform and its applications'' (World Scientific, London, 2005) ISBN 978-9812563767</ref><ref>[http://stacks.iop.org/0029-5515/51/053022 B.A. Carreras et al., ''Reconstruction of intermittent waveforms associated with the zonal flow at the transition leading to the edge shear flow layer'', Nucl. Fusion '''51''' (2011) 053022]</ref>
* [[:Wikipedia:Hilbert-Huang transform|Hilbert-Huang transform]] <ref>N. Huang and S. Shen, ''Hilbert-Huang transform and its applications'' (World Scientific, London, 2005) ISBN 978-9812563767</ref><ref>[http://stacks.iop.org/0029-5515/51/053022 B.A. Carreras et al., ''Reconstruction of intermittent waveforms associated with the zonal flow at the transition leading to the edge shear flow layer'', Nucl. Fusion '''51''' (2011) 053022]</ref>
* Causality detection <ref>[[doi:10.1088/0029-5515/54/2/023011|B.Ph. van Milligen, G. Birkenmeier, M. Ramisch, T. Estrada, C. Hidalgo, and A. Alonso, ''Causality detection and turbulence in fusion plasmas'', Nucl. Fusion '''54''' (2014), 023011]]</ref>


=== Self-similarity ===
=== Self-similarity ===

Revision as of 12:16, 18 February 2014

This page collects information on data analysis techniques used in fusion research.

Temporal analysis

Linear analysis

Non-linear analysis

Self-similarity

Spatial analysis

Most of the techniques listed under 'temporal analysis' can of course be applied to spatial data.

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

Error propagation

References