public NeuronLayer(int iCount, int nCount)
{
Neurons = new Neuron[nCount];
InputCount = iCount;
for (int i = 0; i < nCount; i++)
{
Neurons[i] = new T.Neuron(iCount);
}
}
/// <summary>
/// Create a neuron based on a template
/// </summary>
/// <param name="neuron"></param>
public Neuron(T.Neuron neuron, Activation aF = null)
{
int dendritesCount = neuron.Dendrites;
Dendrites = new float[dendritesCount];
Weights = new float[dendritesCount];
for (int i = 0; i < dendritesCount; i++)
{
Weights[i] = (float)Rng.GetRng() * -0.1f; /// Will change range dependent into AF
}
Bias = 1; //(float) rng.getRng();
ActivationFunction = aF ?? new Logistic();
LearningRate = (float)Rng.GetRng() * 0.05f;
}
