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author | Ilya Popov <ilia.b.popov@gmail.com> | 2015-10-28 09:52:55 +0000 |
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committer | Ilya Popov <ilia.b.popov@gmail.com> | 2015-10-28 09:52:55 +0000 |
commit | 1a842c0dc441cca1bd66a516b16d7fe6a4c0ba26 (patch) | |
tree | eabdc174e7c54810e45a0045d3f523f2a45242a3 /doc/TutorialSparse.dox | |
parent | 85313048581d22901c7940a46bd41b19e88ff47c (diff) |
Fix typo in TutorialSparse: laplace equation contains gradient symbol (\nabla) instead of laplacian (\Delta).
Diffstat (limited to 'doc/TutorialSparse.dox')
-rw-r--r-- | doc/TutorialSparse.dox | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/TutorialSparse.dox b/doc/TutorialSparse.dox index 835c59354..fb07adaa2 100644 --- a/doc/TutorialSparse.dox +++ b/doc/TutorialSparse.dox @@ -83,7 +83,7 @@ There is no notion of compressed/uncompressed mode for a SparseVector. \section TutorialSparseExample First example -Before describing each individual class, let's start with the following typical example: solving the Laplace equation \f$ \nabla u = 0 \f$ on a regular 2D grid using a finite difference scheme and Dirichlet boundary conditions. +Before describing each individual class, let's start with the following typical example: solving the Laplace equation \f$ \Delta u = 0 \f$ on a regular 2D grid using a finite difference scheme and Dirichlet boundary conditions. Such problem can be mathematically expressed as a linear problem of the form \f$ Ax=b \f$ where \f$ x \f$ is the vector of \c m unknowns (in our case, the values of the pixels), \f$ b \f$ is the right hand side vector resulting from the boundary conditions, and \f$ A \f$ is an \f$ m \times m \f$ matrix containing only a few non-zero elements resulting from the discretization of the Laplacian operator. <table class="manual"> |