From a79abb5db18372285a517000d3916512ad187c47 Mon Sep 17 00:00:00 2001
From: Michael Mandl <mandlm@molez.net>
Date: Sat, 17 Oct 2015 22:05:27 +0200
Subject: [PATCH] First implementation of weight updates. Very slow rate of
 change in the output value.

---
 Layer.cpp  | 17 ++++++++++++++++-
 Layer.h    |  2 +-
 Neuro.cpp  | 23 +++++++++++++----------
 Neuron.cpp | 10 ++++++++++
 Neuron.h   |  3 +++
 5 files changed, 43 insertions(+), 12 deletions(-)

diff --git a/Layer.cpp b/Layer.cpp
index 466dd84..c68c135 100644
--- a/Layer.cpp
+++ b/Layer.cpp
@@ -51,6 +51,21 @@ void Layer::connectTo(const Layer & nextLayer)
 	}
 }
 
-void Layer::updateInputWeights(const Layer & prevLayer)
+void Layer::updateInputWeights(Layer & prevLayer)
 {
+	static const double trainingRate = 0.8;
+
+	for (size_t currentLayerIndex = 0; currentLayerIndex < size() - 1; ++currentLayerIndex)
+	{
+		Neuron &targetNeuron = at(currentLayerIndex);
+
+		for (size_t prevLayerIndex = 0; prevLayerIndex < prevLayer.size(); ++prevLayerIndex)
+		{
+			Neuron &sourceNeuron = prevLayer.at(prevLayerIndex);
+
+			sourceNeuron.setOutputWeight(currentLayerIndex, 
+				sourceNeuron.getOutputWeight(currentLayerIndex) + 
+				sourceNeuron.getOutputValue() * targetNeuron.getGradient() * trainingRate);
+		}
+	}
 }
diff --git a/Layer.h b/Layer.h
index 8251a20..a3f118f 100644
--- a/Layer.h
+++ b/Layer.h
@@ -14,5 +14,5 @@ public:
 	double getWeightedSum(int outputNeuron) const;
 	void connectTo(const Layer & nextLayer);
 
-	void updateInputWeights(const Layer &prevLayer);
+	void updateInputWeights(Layer &prevLayer);
 };
diff --git a/Neuro.cpp b/Neuro.cpp
index 7757734..7803bc8 100644
--- a/Neuro.cpp
+++ b/Neuro.cpp
@@ -14,18 +14,21 @@ int main()
 
 		Net myNet({ inputValues.size(), 4, targetValues.size() });
 
-		myNet.feedForward(inputValues);
-
-		std::vector<double> outputValues = myNet.getOutput();
-
-		std::cout << "Result: ";
-		for (double &value : outputValues)
+		for (int i = 0; i < 20; ++i)
 		{
-			std::cout << value << " ";
-		}
-		std::cout << std::endl;
+			myNet.feedForward(inputValues);
 
-		myNet.backProp(targetValues);
+			std::vector<double> outputValues = myNet.getOutput();
+
+			std::cout << "Result: ";
+			for (double &value : outputValues)
+			{
+				std::cout << value << " ";
+			}
+			std::cout << std::endl;
+
+			myNet.backProp(targetValues);
+		}
 	}
 	catch (std::exception &ex)
 	{
diff --git a/Neuron.cpp b/Neuron.cpp
index e57782e..7083f99 100644
--- a/Neuron.cpp
+++ b/Neuron.cpp
@@ -84,3 +84,13 @@ double Neuron::getGradient() const
 	return gradient;
 }
 
+double Neuron::getOutputWeight(size_t index) const
+{
+	return outputWeights.at(index);
+}
+
+void Neuron::setOutputWeight(size_t index, double value)
+{
+	outputWeights.at(index) = value;
+}
+
diff --git a/Neuron.h b/Neuron.h
index 862c17d..c0356d3 100644
--- a/Neuron.h
+++ b/Neuron.h
@@ -25,6 +25,9 @@ public:
 
 	double getGradient() const;
 
+	double getOutputWeight(size_t index) const;
+	void setOutputWeight(size_t index, double value);
+
 private:
 	static double transferFunction(double inputValue);
 	static double transferFunctionDerivative(double inputValue);