private void Signals(float[] output)
{
float[] dif = new float[OutputNodes];
for (int i = 0; i < OutputNodes; i++)
{
dif[i] = Output[i] - output[i];
}
for (int j = 0; j < OutputNodes; j++)
{
mSignals[Length - 1][j] = Mathn.DifSoftmax(Output[j]) * dif[j];
}
for (int l = Length - 2; l >= 0; l--)
{
for (int j = 0; j < Nodes[l]; j++)
{
float sum = 0;
for (int k = 0; k < Nodes[l + 1]; k++)
{
sum += Weigths[l + 1][k][j] * mSignals[l + 1][k];
}
mSignals[l][j] = Mathn.DifSigmoid(mValues[l][j]) * sum; //Check Value
}
}
}
public float[] FeedForward(float[] input)
{
Input = input;
for (int l = 0; l < Length; l++)
{
for (int j = 0; j < Nodes[l]; j++)
{
mValues[l][j] = 0;
if (l == 0)
{
for (int i = 0; i < InputNodes; i++)
{
mValues[l][j] += Input[i] * Weigths[l][j][i];
}
}
else
{
for (int i = 0; i < Nodes[l - 1]; i++)
{
mValues[l][j] += mValues[l - 1][i] * Weigths[l][j][i];
}
}
if (l < Length - 1)
{
mValues[l][j] = Mathn.Sigmoid(mValues[l][j]);
}
}
}
mValues[Length - 1] = Mathn.Softmax(mValues[Length - 1]);
Output = mValues[Length - 1];
return(Output);
}
