diff --git a/matlab/README.md b/matlab/README.md
index 691d1a9ffdc49c4b992f4109d6834b40263567dc..1785b6a1fce91b988d342de1aad6cb896d571467 100644
--- a/matlab/README.md
+++ b/matlab/README.md
@@ -7,13 +7,13 @@ filtering out. More precisely, it is a Matlab implementation of the algorithms
 from *Time-frequency fading algorithms based on Gabor multipliers, by,
 A. Marina Kr�m�, Valentin Emiya, Caroline Chaux, and Bruno Torr�sani, 2020*. 
 
-For more information please contact ama-marina.kreme@univ-amu.fr
+For more information please contact ama-marina.kreme@univ-amu.fr/valentin.emiya@lis-lab.fr
 
 ## Installation
 
 Download the folder "tff2020" into the directory of your choice. 
 Then within MATLAB go to file >> Set path... and add the directory containing
- "tff2020/matlab" to the list (if it isn't already). 
+"tff2020/matlab" to the list (if it isn't already). 
 
 
 ## Dependencies
@@ -25,12 +25,21 @@ which can be downloaded  at  https://ltfat.github.io
 
 See the documentation.
 
-To reproduce figures on the aforementioned paper, go to the
-following directory : "tfgm/scripts" and then run the file 
-**solve_1area_cuicui.m**
+To reproduce the aforementioned paper figures:
 
-You can also run the scripts **solve_all_tff1.m**,
-**solve_all_tffP.m** for more experiments 
+- Figure 1 and 2 can be reproduced by running 
+**tff2020/matlab/tfgm/scripts/exp_gabmul_eigs_properties.m**
+
+- Figure 3 can be reproduced by running
+**tff2020/matlab/tfgm/scripts/rank_estimation_halko_vs_eigs_gausswin.m**
+
+- Figure 4 and 5 can be reproduced by running
+**tff2020/matlab/tfgm/scripts/exp_tff1_car_bird.m**
+
+You can also run the scripts 
+**tff2020/matlab/tfgm/scripts/exp_all_tff1.m** et
+**tff2020/matlab/tfgm/scripts/exp_all_tffP.m**
+for more experiments 
 
 ## Copyright � 2019-2020
 
@@ -42,6 +51,8 @@ You can also run the scripts **solve_all_tff1.m**,
 ## Contributors
 
 - [A. Marina Kr�m�](ama-marina.kreme@univ-amu.fr)
+- [Valentin Emiya](valentin.emiya@lis-lab.fr)
+