/// <summary>
/// Calculates weights for the hopfield net to learn the specified training
/// set
/// </summary>
/// <param name="trainingSet">
/// training set to learn </param>
public override void learn(DataSet trainingSet)
{
int M = trainingSet.size();
int N = neuralNetwork.getLayerAt(0).NeuronsCount;
Layer hopfieldLayer = neuralNetwork.getLayerAt(0);
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
if (j == i)
{
continue;
}
Neuron ni = hopfieldLayer.getNeuronAt(i);
Neuron nj = hopfieldLayer.getNeuronAt(j);
Connection cij = nj.getConnectionFrom(ni);
Connection cji = ni.getConnectionFrom(nj);
double w = 0;
for (int k = 0; k < M; k++)
{
DataSetRow trainingSetRow = trainingSet.getRowAt(k);
double pki = trainingSetRow.Input[i];
double pkj = trainingSetRow.Input[j];
w = w + pki * pkj;
} // k
cij.Weight.Value = w;
cji.Weight.Value = w;
} // j
} // i
}
