public float[] compete(HiddenLayer hiddenLayer)
{
NeuronList list = hiddenLayer.getHiddenLayerNeurons();
IEnumerator listEnum = list.GetEnumerator();
float[] x = new float[list.Count];
int i = 0;
while (listEnum.MoveNext())
{
x[i++] = ((HiddenLayerNeuron)listEnum.Current).getOutput();
}
double max = x[0];
int maxIndex = 0;
for (int j = x.Length - 1; j > 0; j--)
{
if (max < x[j])
{
maxIndex = j;
}
max = Math.Max(max, x[j]);
}
for (int k = 0; k < x.Length; k++)
{
x[k] = 0;
if (k == maxIndex)
{
x[k] = 1;
}
}
return(x);
}
public static NeuronList createNeurons(int[,] w, short LIST_TYPE)
{
neuronList = new NeuronList(LIST_TYPE);
for (int i = 0; i < w.GetLength(0); i++)
{
Neuron.Synapse[] s = new Neuron.Synapse[w.GetLength(1)];
for (int j = 0; j < w.GetLength(1); j++)
{
s[j] = new Neuron.Synapse(w[i, j]);
}
neuronList.Add(new OutputLayerNeuron(s));
}
return(neuronList);
}
public OutputLayer(int [,] weights)
{
outputNeurons = NeuronFectory.createNeurons(weights, 2);
}
public HiddenLayer(double [,] weights)
{
hiddenLayerNeurons = NeuronFectory.createNeurons(weights, 1);
}