diff --git a/NeuralNetwork/Examples/Utilities/NARX_Network.mo b/NeuralNetwork/Examples/Utilities/NARX_Network.mo
index be2443e..88b3c82 100644
--- a/NeuralNetwork/Examples/Utilities/NARX_Network.mo
+++ b/NeuralNetwork/Examples/Utilities/NARX_Network.mo
@@ -1,9 +1,10 @@
 within NeuralNetwork.Examples.Utilities;
-
 block NARX_Network
   // This represents a three layer neural network with a given time delay
 
-  extends NeuralNetwork.Networks.Interfaces.Network(u = layer_scale.u, y = layer_3.y);
+  extends NeuralNetwork.Networks.Interfaces.Network(
+    redeclare Modelica.Blocks.Interfaces.RealInput u[size(layer_1.u,1)],
+    redeclare Modelica.Blocks.Interfaces.RealOutput y[size(layer_3.y,1)]);
 
   NeuralNetwork.Layer.Preprocessing.Scale layer_scale(
     min = {
@@ -106,6 +107,9 @@ block NARX_Network
     redeclare function f = NeuralNetwork.ActivationFunctions.Id
    ) annotation(Placement(transformation(origin = {92, 0}, extent = {{-30, -30}, {30, 30}})));
 equation
+  connect( u, layer_scale.u);
+  connect( layer_3.y, y);
+
   connect(layer_scale.y, layer_1.u) annotation(
     Line(points = {{-74, 0}, {-52, 0}}, color = {0, 0, 127}, thickness = 0.5));
   connect(layer_1.y, layer_2.u) annotation(
diff --git a/NeuralNetwork/Examples/Utilities/SimpleNetwork.mo b/NeuralNetwork/Examples/Utilities/SimpleNetwork.mo
index d5c9ff1..cd45c84 100644
--- a/NeuralNetwork/Examples/Utilities/SimpleNetwork.mo
+++ b/NeuralNetwork/Examples/Utilities/SimpleNetwork.mo
@@ -1,7 +1,6 @@
 within NeuralNetwork.Examples.Utilities;
-
 block SimpleNetwork "Neural Network approximating y = u*u + 0.5*u - 2.0 on interval [-1,1]"
-  extends NeuralNetwork.Networks.Interfaces.SISO(final u = inputLayer.u[1], final y = outputLayer.y[1]);
+  extends NeuralNetwork.Networks.Interfaces.SISO;
   Layer.Dense inputLayer(
     weights = layer_1_weights,
     bias = layer_1_bias,
@@ -20,6 +19,9 @@ block SimpleNetwork "Neural Network approximating y = u*u + 0.5*u - 2.0 on inter
   parameter Real[1,2] layer_2_weights = {{-4.513856227908402, 2.4932885356708683}};
   parameter Real[1] layer_2_bias = {3.897109323824147};
 equation
+  connect( u, inputLayer.u[1]);
+  connect( outputLayer.y[1], y);
+
   connect(inputLayer.y, outputLayer.u) annotation(
     Line(points = {{-48, 0}, {30, 0}}, color = {0, 0, 127}, thickness = 0.5));
   annotation(
diff --git a/NeuralNetwork/Layer/Interfaces/Layer.mo b/NeuralNetwork/Layer/Interfaces/Layer.mo
index 23b8060..dcd87eb 100644
--- a/NeuralNetwork/Layer/Interfaces/Layer.mo
+++ b/NeuralNetwork/Layer/Interfaces/Layer.mo
@@ -1,6 +1,5 @@
 within NeuralNetwork.Layer.Interfaces;
-
-partial model Layer
+partial block Layer
   // Topology of the neural network
   parameter Integer numInputs   "Specification of the inputs of the layer";
   parameter Integer numNeurons  "Number of neurons in the layer";