public void Backward(MatrixFloat expected)
{
//error = (1/2)*(actual-expected)^2
var lastLayer = neuronLayers[neuronLayers.Count - 1];
var deltaErrorOut = 0.1f * (lastLayer.Neurons - expected) * lastLayer.ActivateDeriv();
lastLayer.Gradient = deltaErrorOut;
var update = neuronLayers[neuronLayers.Count - 2].Activate().Transpose().Multiply(deltaErrorOut);
weightLayers[neuronLayers.Count - 2].Gradient = update;
var prevDelta = deltaErrorOut;
for (int i = neuronLayers.Count - 2; i >= 1; i--)
{
var dLayer = prevDelta.Multiply(weightLayers[i].Weights.Transpose()) * neuronLayers[i].ActivateDeriv();
neuronLayers[i].Gradient = dLayer;
update = neuronLayers[i - 1].Activate().Transpose().Multiply(dLayer);
weightLayers[i - 1].Gradient = update;
prevDelta = dLayer;
}
for (int i = 0; i < weightLayers.Count; i++)
{
weightLayers[i].Weights -= weightLayers[i].Gradient;
}
}
public MatrixFloat Apply(Func <float, float> func)
{
var a = new MatrixFloat(Rows, Columns);
for (int i = 0; i < Rows * Columns; i++)
{
a._array[i] = func(_array[i]);
}
return(a);
}
public MatrixFloat Transpose()
{
var t = new MatrixFloat(Columns, Rows);
for (int row = 0; row < Rows; row++)
{
for (int column = 0; column < Columns; column++)
{
t[column, row] = this[row, column];
}
}
return(t);
}
public MatrixFloat Substract(MatrixFloat other)
{
#if DEBUG
if (Columns != other.Columns || Rows != other.Rows)
{
throw new Exception($"Columns {Columns} does not equal other.Columns {other.Columns} or Rows {Rows} does not equal other.Rows {other.Rows}");
}
#endif
var a = new MatrixFloat(Rows, Columns);
for (int i = 0; i < Rows * Columns; i++)
{
a._array[i] = _array[i] - other._array[i];
}
return(a);
}
public MatrixFloat Multiply(MatrixFloat other)
{
#if DEBUG
if (Columns != other.Rows)
{
throw new Exception($"Columns {Columns} does not equal other.Rows {other.Rows}");
}
#endif
var result = new MatrixFloat(Rows, other.Columns);
for (int cColumn = 0; cColumn < result.Columns; cColumn++)
{
for (int cRow = 0; cRow < result.Rows; cRow++)
{
for (int i = 0; i < Columns; i++)
{
result[cRow, cColumn] += this[cRow, i] * other[i, cColumn];
}
}
}
return(result);
}