From 541284f6f1bf7d4a76daac8a52850c7162a765cb Mon Sep 17 00:00:00 2001
From: mcarrier <mcarrier@636b058d-ea47-450e-bf9e-a15bfbe3eedb>
Date: Mon, 23 Apr 2018 15:22:13 +0000
Subject: git-svn-id:
 svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/kernels@3387
 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 3fe2ae4af0c7cadf507fc5148c05dcf664c5e151
---
 .../doc/Persistence_representations_doc.h                            | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

(limited to 'src/Persistence_representations/doc/Persistence_representations_doc.h')

diff --git a/src/Persistence_representations/doc/Persistence_representations_doc.h b/src/Persistence_representations/doc/Persistence_representations_doc.h
index 6d4cc96c..ca283017 100644
--- a/src/Persistence_representations/doc/Persistence_representations_doc.h
+++ b/src/Persistence_representations/doc/Persistence_representations_doc.h
@@ -24,7 +24,6 @@
 #define DOC_GUDHI_STAT_H_
 
 namespace Gudhi {
-
 namespace Persistence_representations {
 
 /**  \defgroup Persistence_representations Persistence representations
@@ -254,11 +253,11 @@ namespace Persistence_representations {
 
 
 
-\section sec_persistence_kernels Kernels on Persistence Diagrams
+\section sec_persistence_kernels Kernels on persistence diagrams
  <b>Reference manual:</b> \ref Gudhi::Persistence_representations::Sliced_Wasserstein <br>
  <b>Reference manual:</b> \ref Gudhi::Persistence_representations::Persistence_weighted_gaussian <br>
 
- Kernels for Persistence Diagrams can be regarded as infinite-dimensional vectorizations. More specifically,
+ Kernels for persistence diagrams can be regarded as infinite-dimensional vectorizations. More specifically,
  they are similarity functions whose evaluations on pairs of persistence diagrams equals the scalar products
  between images of these pairs under a map \f$\Phi\f$ taking values in a specific (possibly non Euclidean) Hilbert space \f$k(D_i, D_j) = \langle \Phi(D_i),\Phi(D_j)\rangle\f$.
  Reciprocally, classical results of learning theory ensure that such a \f$\Phi\f$ exists for a given similarity function \f$k\f$ if and only if \f$k\f$ is <i>positive semi-definite</i>.
-- 
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