public void ProcessError(Vector error)
{
Matrix weightUpdate = error.Times(lastInput.Transpose());
layer.AcceptNewWeightUpdate(weightUpdate);
Vector biasUpdate = layer.GetBiasVector().Plus(error);
layer.AcceptNewBiasUpdate(biasUpdate);
}
public static Vector CalculateBiasUpdates(LayerSensitivity layerSensitivity,
double alpha)
{
Layer layer = layerSensitivity.GetLayer();
Matrix biasUpdateMatrix
= layerSensitivity.GetSensitivityMatrix()
.Times(alpha)
.Times(-1.0);
Vector result = new Vector(biasUpdateMatrix.GetRowDimension());
for (int i = 0; i < biasUpdateMatrix.GetRowDimension(); ++i)
{
result.SetValue(i, biasUpdateMatrix.Get(i, 0));
}
layer.AcceptNewBiasUpdate(result.CopyVector());
return(result);
}
public Vector CalculateBiasUpdates(LayerSensitivity layerSensitivity,
double alpha,
double momentum)
{
Layer layer = layerSensitivity.GetLayer();
Matrix biasUpdateMatrixWithoutMomentum = layerSensitivity.GetSensitivityMatrix().Times(alpha).Times(-1.0);
Matrix biasUpdateMatrixWithMomentum
= layer.GetLastBiasUpdateVector()
.Times(momentum)
.Plus(biasUpdateMatrixWithoutMomentum
.Times(1.0 - momentum));
Vector result = new Vector(biasUpdateMatrixWithMomentum.GetRowDimension());
for (int i = 0; i < biasUpdateMatrixWithMomentum.GetRowDimension(); ++i)
{
result.SetValue(i, biasUpdateMatrixWithMomentum.Get(i, 0));
}
layer.AcceptNewBiasUpdate(result.CopyVector());
return(result);
}