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-rw-r--r--Eigen/src/SVD/JacobiSVD.h2
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.