public NeuralLayer(int inputSize, int neuronsSize, bool randomWeights, double[] randomWeightsLimits, TransitionFunction tf, bool useBias)
{
neurons = new Neuron[neuronsSize];
for (int j = 0; j < neuronsSize; j++)
{
double[] weights = new double[inputSize];
neurons[j] = new Neuron(weights, 0, tf);
if (randomWeights)
{
neurons[j].RandomFill(randomWeightsLimits, useBias);
}
}
}
private void Init(int inputSize, int neuronsSize, bool randomWeights, double[] randomWeightsLimits, int neighbourhoodDimension)
{
neurons = new Neuron[neuronsSize];
for (int j = 0; j < neuronsSize; j++)
{
double[] weights = new double[inputSize];
neurons[j] = new Neuron(weights, 0);
if (randomWeights)
neurons[j].RandomFill(randomWeightsLimits, true);
}
int length = (int)Math.Ceiling(Math.Pow(neuronsSize, 1.0 / neighbourhoodDimension));
for (int i = 0; i < neuronsSize; i++)
{
double[] pos = new double[neighbourhoodDimension];
int p = i;
for (int j = 0; j < neighbourhoodDimension - 1; j++)
{
pos[j] = p % length;
p /= length;
}
pos[neighbourhoodDimension - 1] = p;
neurons[i].Position = pos;
}
}
public KohonenLayer(Neuron[] neurons)
{
this.neurons = neurons;
}
public NeuralLayer(Neuron[] neurons)
{
this.neurons = neurons;
}
