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Diffstat (limited to 'Eigen/src/SVD/JacobiSVD.h')
-rw-r--r-- | Eigen/src/SVD/JacobiSVD.h | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/Eigen/src/SVD/JacobiSVD.h b/Eigen/src/SVD/JacobiSVD.h index 71d810f09..f12494dbc 100644 --- a/Eigen/src/SVD/JacobiSVD.h +++ b/Eigen/src/SVD/JacobiSVD.h @@ -234,7 +234,7 @@ struct ei_qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, Precon * \include JacobiSVD_basic.cpp * Output: \verbinclude JacobiSVD_basic.out * - * This %JacobiSVD class a two-sided Jacobi R-SVD decomposition, ensuring optimal reliability and accuracy. The downside is that it's slower than + * This JacobiSVD class is a two-sided Jacobi R-SVD decomposition, ensuring optimal reliability and accuracy. The downside is that it's slower than * bidiagonalizing SVD algorithms for large square matrices; however its complexity is still \f$ O(n^2p) \f$ where \a n is the smaller dimension and * \a p is the greater dimension, meaning that it is still of the same order of complexity as the faster bidiagonalizing R-SVD algorithms. * In particular, like any R-SVD, it takes advantage of non-squareness in that its complexity is only linear in the greater dimension. |