[eigen] Adapting code from OpenCV (a seemingly much faster SVD)

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After performing some comparisons with Eigen's SVD (see attachment), I am wondering whether it might be of interest or possible at all to use the decomposition from OpenCV. I would volunteer :) to port it - maybe in a first step as a new SVD class in the 'disabled' folder that enables repeatable comparisons. This would obviously only make sense in case it is possible at all to use the code I have from the OpenCV lib. Actually, I ported the code before to our own hand-crafted linear algebra lib. But for Eigen, one definitely needs to take care of license issues. Since I have very little knowledge about these things, I am wondering whether somebody could comment on the attached license file - afaik, it is the same as when I copied the SVD code.

The test results from the attached PDF were generated with double precision, dynamic size matrices of dimensions 25x25 up to 200x200 - each decomposition has been run 100 times. The graph contains the mean decomposition time in seconds for different matrix sizes (y-axis). The standard deviations in the legend are the deviations that occured while performing one and the same decomposition 100 times.

Any comments would be welcome...



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Attachment: svd.pdf
Description: Adobe PDF document

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