private void ComputeHiddenLayersProp(float[] outputsWished)
{
// Manage error for HiddenLayers values
for (int k = HiddenLayerNb - 1; k >= 0; --k)
{
for (int i = 0; i < NeuronsPerHiddenLayer; ++i)
{
Neuron oneHidden = HiddenLayers[k].Neurons[i];
float totalError = 0.0f;
// Modify values of last HiddenLayer using Output values
for (int j = 0; j < oneHidden.NextNeuronsNb; ++j)
{
Neuron.Link link = oneHidden.NextLinks[j];
totalError += link.Error * link.Weight;
}
for (int j = 0; j < oneHidden.PreviousNeuronsNb; ++j)
{
float delta = totalError * oneHidden.ActivationValue * (1.0f - oneHidden.ActivationValue);
Neuron.Link link = oneHidden.PreviousNeurons[j].GetLinkTowards(oneHidden);
link.Error = delta;
}
}
}
}
private void ComputeFirstOutputBackprop(float[] outputsWished)
{
// Manage error with Output values
for (int i = 0; i < OutputNb; ++i)
{
Neuron oneOutput = OutputLayer.Neurons[i];
// Modify values of last HiddenLayer using Output values
for (int j = 0; j < NeuronsPerHiddenLayer; ++j)
{
float delta = -(outputsWished[i] - oneOutput.ActivationValue)
* oneOutput.ActivationValue
* (1.0f - oneOutput.ActivationValue);
Neuron.Link link = HiddenLayers[HiddenLayerNb - 1].Neurons[j].GetLinkTowards(oneOutput);
link.Error = delta;
}
}
}
