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Archetypal analysis of spatio-temporal dynamics. (English) Zbl 0900.76189

Summary: A comparison is made between the principal component or Karhunen-Loève decomposition (KL) of two sets of spatio-temporal data (one numerical, the other experimental) and a new procedure called archetypal analysis. Archetypes characterize the convex hull of the data set and the data set can be reconstructed in terms of these values. Archetypes may be more appropriate than KL when the data do not have elliptical distributions, and are often well-suited to studying regimes in which the system spends a long time near a ”steady” state, punctuated with quick excursions to outliers in the data set, which may represent intermittency. Other advantages and disadvantages of each method are discussed.

MSC:

76F99 Turbulence
37N99 Applications of dynamical systems

Software:

KLTOOL
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References:

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