diff --git a/book/src/AI-Models/Recurrent_Neural_Network/Recurrent-Neural-Network.md b/book/src/AI-Models/Recurrent_Neural_Network/Recurrent-Neural-Network.md
index 08841f117f24bfb67e39df051c9549e4674528c4..8029b975506116460d8243ea26c8c4cb27febb6a 100644
--- a/book/src/AI-Models/Recurrent_Neural_Network/Recurrent-Neural-Network.md
+++ b/book/src/AI-Models/Recurrent_Neural_Network/Recurrent-Neural-Network.md
@@ -16,3 +16,7 @@ As previously stated a recurrent neural network uses sequences and node connecti
 
 ![Unfold RNN](./Recurrent_neural_network_unfold.png "Unfold RNN")
 Source: <https://en.wikipedia.org/wiki/Recurrent_neural_network> 05.01.2022
+
+## References
+
+{{#include ../../References.md:Recurrent_neural_network}}
diff --git a/book/src/References.md b/book/src/References.md
index d0a6de3a6894b343c5df049bb72af956dbd137dd..e3c9765c19cdcfe29995ef54ece958f1d449556a 100644
--- a/book/src/References.md
+++ b/book/src/References.md
@@ -104,4 +104,10 @@ ANCHOR: Multi_Layer_Perceptron
 [1] [How Neural Networks Solve the XOR Problem (last accessed on 17.01.2022)](https://towardsdatascience.com/how-neural-networks-solve-the-xor-problem-59763136bdd7)
 ANCHOR_END: Multi_Layer_Perceptron
 
+### Recurrent Neural Network
+ANCHOR: Recurrent_neural_network
+[1] [Recurrent Neural Networks (last accessed on 18.01.2022)] (https://www.ibm.com/cloud/learn/recurrent-neural-networks)\
+[2] [Recurrent Neural Networks cheatsheet (last accessed on 18.01.2022)] (https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-recurrent-neural-networks)
+ANCHOR_END: Recurrent_neural_network
+
 ANCHOR_END: ALL