diff --git a/doc/ipython-notebooks/ica/bss_audio.ipynb b/doc/ipython-notebooks/ica/bss_audio.ipynb
index 63605686504..c40ea3634fd 100644
--- a/doc/ipython-notebooks/ica/bss_audio.ipynb
+++ b/doc/ipython-notebooks/ica/bss_audio.ipynb
@@ -1,6 +1,7 @@
 {
  "metadata": {
-  "name": ""
+  "name": "",
+  "signature": "sha256:77eb097c6023f842dff60d64dc21c876918a0b7ac1d94866dff061d571eddf4a"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -27,7 +28,7 @@
      "cell_type": "markdown",
      "metadata": {},
      "source": [
-      "In this notebook I am going to show you how we can do Blind Source Separation (BSS) using algorithms available in the Shogun Machine Learning Toolbox. What is Blind Source Separation? BSS is the separation of a set of source signals from a set of mixed signals."
+      "This notebook illustrates <a href=\"http://en.wikipedia.org/wiki/Blind_signal_separation\">Blind Source Seperation</a>(BSS) on audio signals using <a href=\"http://en.wikipedia.org/wiki/Independent_component_analysis\">Independent Component Analysis</a> (ICA) in Shogun. We generate a mixed signal and try to seperate it out using Shogun's implementation of ICA & BSS called <a href=\"http://www.shogun-toolbox.org/doc/en/3.0.0/classshogun_1_1CJade.html\">JADE</a>."
      ]
     },
     {