From 00e0224a875925f4e41fc5e8226a2e97c29f6925 Mon Sep 17 00:00:00 2001
From: Sylvain Calinon <sylvain.calinon@idiap.ch>
Date: Wed, 20 Jul 2022 09:12:02 +0200
Subject: [PATCH] TTGO example added

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index b076026..1d84025 100644
--- a/README.md
+++ b/README.md
@@ -234,7 +234,7 @@ All the examples are located in the `demos` folder, and the functions are locate
 | [demo_search01.m](./demos/demo_search01.m) | [[2]](#ref-2) | EM-based stochastic optimization |
 | [demo_spring01.m](./demos/demo_spring01.m) | [[10]](#ref-10) | Influence of the damping ratio in mass-spring-damper systems |
 | [demo_stdPGMM01.m](./demos/demo_stdPGMM01.m) | [[1]](#ref-1) | Parametric Gaussian mixture model (PGMM) used as a task-parameterized model, with DS-GMR employed to retrieve continuous movements |
-| [demo_tensor_TTGO01.m](./demos/demo_tensor_TTGO01.m) | [[11]](#ref-11) | Global optimization with tensor trains (TTGO) |
+| [demo_tensor_TTGO01.m](./demos/demo_tensor_TTGO01.m) | [[12]](#ref-12) | Global optimization with tensor trains (TTGO) |
 | [demo_TPHDDC01.m](./demos/demo_TPHDDC01.m) | [[1]](#ref-1) | Task-parameterized high dimensional data clustering (TP-HDDC) |
 | [demo_TPGMM01.m](./demos/demo_TPGMM01.m) | [[1]](#ref-1) | Task-parameterized Gaussian mixture model (TP-GMM) encoding |
 | [demo_TPGMM_bimanualReaching01.m](./demos/demo_TPGMM_bimanualReaching01.m) | [[1]](#ref-1) | Time-invariant task-parameterized GMM applied to a bimanual reaching task |
-- 
GitLab