From 715607032a1b17effbc531f8fc434515f5733651 Mon Sep 17 00:00:00 2001
From: "Li, Honglin (PG/R - Elec Electronic Eng)" <h.li@surrey.ac.uk>
Date: Thu, 5 Dec 2019 13:39:17 +0000
Subject: [PATCH] Update README.md

---
 README.md | 18 +++++++++++++++++-
 1 file changed, 17 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index fa9cd1a..951a48b 100644
--- a/README.md
+++ b/README.md
@@ -6,6 +6,22 @@ Task Conditional Neural Networks (TCNN) leverage the probabilistic neural networ
 Then produce the task likelihood during the test state to fire the task-specific neurons correspondin to the test sampels. TCNN can detect and 
 learn the new tasks fully-automatically without informing the changes to the model.
 
-
+The schematic diagram of TCNN learning process.
 ![TCNN_Process](/images/TCNN.png)
 
+
+
+## Dependencies
+
+The code is tested on 
+*  Python 3.6.8
+*  Tensorflow '1.13.1'
+*  Keras '2.2.4'
+
+## Reproduce
+To run the experiment, run the '''split_mnist.py''' files via:
+'''python split_mnist.py'''
+
+The result should be similar to the figure below:
+
+![TCNN_Process](/images/result.png)
\ No newline at end of file
-- 
GitLab