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- To: eigen@xxxxxxxxxxxxxxxxxxx
- Subject: Re: [eigen] SVD with singular matrices
- From: Benoit Jacob <jacob.benoit.1@xxxxxxxxx>
- Date: Wed, 29 Sep 2010 10:32:14 -0400
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2010/9/29 <hamelin.philippe@xxxxxxx>:
> Hello,
>
> when updating from eigen2 to eigen3, I found that my pseudo-inverse was not
> working correctly for singular matrices. However, just replacing SVD with
> JacobiSVD makes it work. Before looking further, is there any limitation
> with SVD with singular matrices such as:
>
> [1 1;0 0]
JacobiSVD always works, and is always precise. But it's slow for large matrices.
SVD uses the Golub-Kahan bidiagonalization approach. So it's faster,
but potentially inaccurate for certain singular matrices.
I would be surprised though if the above 2x2 matrix was enough to
expose problems in it. That would be a bug. Can you make a compilable
test case?
Thanks,
Benoit
>
> Thank you,
>
> ------------------------------------
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