MULTIDIMENSIONAL EXTENSION OF SINGULAR SPECTRUM ANALYSIS BASED ON FILTERING INTERPRETATION
2014 ◽
Vol 06
(01)
◽
pp. 1450005
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Keyword(s):
Singular spectrum analysis is a nonparametric spectral decomposition of a time series. The singular spectrum analysis can be viewed as the two-step filtering with the complete set of eigenfilter adaptively constructed from the original time series. Based on this viewpoint, we present a flexible and quite simple algorithm for the singular spectrum analysis which can be applied to the multidimensional data series with arbitrary dimension. We have carried out the decomposition of two-dimensional image data, and the optimally constructed filters are found to be the smoothing or the edge enhancement filters of various type. We have also examined a simple example for the decomposition of 3D data.
2012 ◽
Vol 04
(04)
◽
pp. 1250023
◽
2016 ◽
Vol 08
(01)
◽
pp. 1650002
◽
2013 ◽
Vol 114
◽
pp. 126-136
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Keyword(s):
2011 ◽
pp. 1335-1337
◽