public double UpdateWeights(double[] pattern, KohonenNeuron winner, int it)
{
double sum = 0;
for (int i = 0; i < Weights.Length; i++)
{
double delta = LearningRate(it) * Gauss(winner, it) * (pattern[i] - Weights[i]);
Weights[i] += delta;
sum += delta;
}
return(sum / Weights.Length);
}
private double Gauss(KohonenNeuron win, int it)
{
double distance = Math.Sqrt(Math.Pow(win.X - X, 2) + Math.Pow(win.Y - Y, 2));
return(Math.Exp(-Math.Pow(distance, 2) / (Math.Pow(Strength(it), 2))));
}