From 962b30d75e47457b63945663e7a6fed1e085f4d5 Mon Sep 17 00:00:00 2001
From: Benoit Jacob <jacob.benoit.1@gmail.com>
Date: Wed, 30 Jun 2010 19:27:30 -0400
Subject: fix linalg tut; remove the old one

---
 doc/TopicLinearAlgebraDecompositions.dox | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

(limited to 'doc/TopicLinearAlgebraDecompositions.dox')

diff --git a/doc/TopicLinearAlgebraDecompositions.dox b/doc/TopicLinearAlgebraDecompositions.dox
index 1ff0549f9..ad8d0abea 100644
--- a/doc/TopicLinearAlgebraDecompositions.dox
+++ b/doc/TopicLinearAlgebraDecompositions.dox
@@ -249,8 +249,8 @@ namespace Eigen {
 
 \b Notes:
 <ul>
-<li><a name="note1">\b 1: </a>There exist a couple of variants of the LDLT algorithm. Eigen's one produces a pure diagonal matrix, and therefore it cannot handle indefinite matrix, unlike Lapack's one which produces a block diagonal matrix.</li>
-<li><a name="note2">\b 2: </a>Eigenvalues and Schur decompositions rely on iterative algorithms. Their convergence speed depends on how well the eigenvalues are separated.</li>
+<li><a name="note1">\b 1: </a>There exist two variants of the LDLT algorithm. Eigen's one produces a pure diagonal D matrix, and therefore it cannot handle indefinite matrices, unlike Lapack's one which produces a block diagonal D matrix.</li>
+<li><a name="note2">\b 2: </a>Eigenvalues, SVD and Schur decompositions rely on iterative algorithms. Their convergence speed depends on how well the eigenvalues are separated.</li>
 </ul>
 
 \section TopicLinAlgTerminology Terminology
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