private float[] SigmaHidden(float[] input, float[,] wMapOut, float[] sigmaPrev, IFunction activationFunction)
{
activationFunction = activationFunction ?? new Linear();
var xLength = wMapOut.GetLength(0);
var yLength = wMapOut.GetLength(1);
if (xLength != input.Length)
{
throw new ArgumentOutOfRangeException(nameof(wMapOut));
}
if (yLength != sigmaPrev.Length)
{
throw new ArgumentOutOfRangeException(nameof(wMapOut));
}
float[] sigmaHidden = new float[xLength];
Parallel.For(0, xLength, x =>
{
var sigmaSum = 0F;
for (var y = 0; y < yLength; y++)
{
sigmaSum += wMapOut[x, y] * sigmaPrev[y];
}
sigmaHidden[x] = sigmaSum * activationFunction.Derevative(input[x]);
});
return(sigmaHidden);
}
public float[] ApplyDerivativeFunction(float[] vector, IFunction activationFunction)
{
activationFunction = activationFunction ?? new Linear();
var result = new float[vector.Length];
Parallel.For(0, vector.Length, i => { result[i] = activationFunction.Derevative(vector[i]); });
return(result);
}
private float[] SigmaOut(float[] ideal, float[] input, IFunction activationFunction)
{
activationFunction = activationFunction ?? new Linear();
float[] sigmaOut = new float[input.Length];
Parallel.For(0, sigmaOut.Length, i => { sigmaOut[i] = (ideal[i] - activationFunction.Apply(input[i])) * activationFunction.Derevative(input[i]); });
return(sigmaOut);
}