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author | Gael Guennebaud <g.gael@free.fr> | 2018-04-11 10:46:11 +0200 |
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committer | Gael Guennebaud <g.gael@free.fr> | 2018-04-11 10:46:11 +0200 |
commit | e798466871ceef80a5bd78eba460735fca829a8c (patch) | |
tree | 2edc5b16c23c1356d8714bb414227f886c017c5d /doc/LeastSquares.dox | |
parent | c91906b065ddfd80997204e3072bb66bc9297bcd (diff) |
bug #1538: update manual pages regarding BDCSVD.
Diffstat (limited to 'doc/LeastSquares.dox')
-rw-r--r-- | doc/LeastSquares.dox | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/LeastSquares.dox b/doc/LeastSquares.dox index e2191a22f..24dfe4b4f 100644 --- a/doc/LeastSquares.dox +++ b/doc/LeastSquares.dox @@ -16,7 +16,7 @@ equations is the fastest but least accurate, and the QR decomposition is in betw \section LeastSquaresSVD Using the SVD decomposition -The \link JacobiSVD::solve() solve() \endlink method in the JacobiSVD class can be directly used to +The \link BDCSVD::solve() solve() \endlink method in the BDCSVD class can be directly used to solve linear squares systems. It is not enough to compute only the singular values (the default for this class); you also need the singular vectors but the thin SVD decomposition suffices for computing least squares solutions: |