public static RandomHolder GetInstance()
{
if (Instance == null)
{
Instance = new RandomHolder();
}
return(Instance);
}
public Neuron()
{
Weights = new Double[Constants.INPUT_SIZE];
RandomHolder rand = RandomHolder.GetInstance();
WeightBias = 1 / ((rand.getRandomDouble() * 100) + 1);
}
//helper methods
public void generateWeight()
{
RandomHolder rand = RandomHolder.GetInstance();
for (int i = 0; i < Weights.Length; i++)
{
Weights[i] = 1 / ((rand.getRandomDouble() * 100) + 1);
}
}
public void train(int phases)
{
RandomHolder rand = RandomHolder.GetInstance();
for (int i = 0; i < phases; i++)
{
int index = (int)(rand.getRandomDouble() * TrainSet.Count);
TrainingSet t = TrainSet[index];
setInputs(t.getInputs());
adjustWeight(t.getOutputs());
}
}
