/// <summary>
/// Calculate the gradient for a neuron.
/// </summary>
/// <param name="toNeuron">The neuron to calculate for.</param>
private void CalculateNeuronGradient(IFreeformNeuron toNeuron)
{
// Only calculate if layer has inputs, because we've already handled the
// output
// neurons, this means a hidden layer.
if (toNeuron.InputSummation != null)
{
// between the layer deltas between toNeuron and the neurons that
// feed toNeuron.
// also calculate all inbound gradeints to toNeuron
foreach (IFreeformConnection connection in toNeuron
.InputSummation.List)
{
// calculate the gradient
double gradient = connection.Source.Activation
* toNeuron.GetTempTraining(0);
connection.AddTempTraining(0, gradient);
// calculate the next layer delta
IFreeformNeuron fromNeuron = connection.Source;
double sum = fromNeuron.Outputs.Sum(toConnection => toConnection.Target.GetTempTraining(0) * toConnection.Weight);
double neuronOutput = fromNeuron.Activation;
double neuronSum = fromNeuron.Sum;
double deriv = toNeuron.InputSummation
.ActivationFunction
.DerivativeFunction(neuronSum, neuronOutput);
if (FixFlatSopt &&
(toNeuron.InputSummation
.ActivationFunction is ActivationSigmoid))
{
deriv += FlatSpotConst;
}
double layerDelta = sum * deriv;
fromNeuron.SetTempTraining(0, layerDelta);
}
// recurse to the next level
foreach (IFreeformConnection connection in toNeuron
.InputSummation.List)
{
IFreeformNeuron fromNeuron = connection.Source;
CalculateNeuronGradient(fromNeuron);
}
}
}
/// <summary>
/// Calculate the output delta for a neuron, given its difference.
/// Only used for output neurons.
/// </summary>
/// <param name="neuron">The neuron.</param>
/// <param name="diff">The difference.</param>
private void CalculateOutputDelta(IFreeformNeuron neuron,
double diff)
{
double neuronOutput = neuron.Activation;
double neuronSum = neuron.InputSummation.Sum;
double deriv = neuron.InputSummation.ActivationFunction
.DerivativeFunction(neuronSum, neuronOutput);
if (FixFlatSopt &&
(neuron.InputSummation.ActivationFunction is ActivationSigmoid))
{
deriv += FlatSpotConst;
}
double layerDelta = deriv * diff;
neuron.SetTempTraining(0, layerDelta);
}
/// <summary>
/// Calculate the output delta for a neuron, given its difference.
/// Only used for output neurons.
/// </summary>
/// <param name="neuron">The neuron.</param>
/// <param name="diff">The difference.</param>
private void CalculateOutputDelta(IFreeformNeuron neuron,
double diff)
{
double neuronOutput = neuron.Activation;
double neuronSum = neuron.InputSummation.Sum;
double deriv = neuron.InputSummation.ActivationFunction
.DerivativeFunction(neuronSum, neuronOutput);
if (FixFlatSopt
&& (neuron.InputSummation.ActivationFunction is ActivationSigmoid)) {
deriv += FlatSpotConst;
}
double layerDelta = deriv * diff;
neuron.SetTempTraining(0, layerDelta);
}
