Docuimentation updated, ready for DBM integration

MelJan · Oct 14, 2018 · 44b1fc4 · 44b1fc4
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diff --git a/docs/tutorials/ICA_natural_images.rst b/docs/tutorials/ICA_natural_images.rst
@@ -56,7 +56,7 @@ the optimal grating, here for 20 filters
 as well as the corresponding tuning curves, which show the responds/activities as a function frequency in pixels/cycle (left) and angle in rad (right).
 
 .. figure:: images/ICA_tuning.png
-   :scale: 75 %
+   :scale: 50 %
    :alt: ICA  fiter's tuning curves
    :align: center
 

diff --git a/docs/welcome.rst b/docs/welcome.rst
@@ -12,10 +12,11 @@ News
 - Unittests added, examples
 - tutorials added
 
-- Upcoming (mid-term): Feed Forward neural networks will be added
+- Upcoming (short-term): Deep Boltzmann machines will be added
 
-- Future: MDP integration
-- Future: Deep Boltzmann machines will be added
+- Upcoming (short-term): Feed Forward neural networks will be added
+
+- Future:
 - Future: RBM/DBM in tensorFlow
 
 Features index
@@ -111,10 +112,10 @@ If you want to use PyDeep in your publication, you can cite it as follows.
 
 .. code-block:: latex
 
-   @misc{melchior2017pydeep,
+   @misc{melchior2018pydeep,
          title={PyDeep},
          author={Melchior, Jan},
-         year={2017},
+         year={2018},
          publisher={GitHub},
          howpublished={\url{https://github.com/MelJan/PyDeep.git}},
         }