public Kernel(int size, int depth, LearningRateAnnealerType type)
{
_learningRateAnnealers = new ILearningRateAnnealer[depth, size, size];
_learningRateAnnealers.ForEach((i, j, k) => _learningRateAnnealers[i, j, k] = LearningRateAnnealerFactory.Produce(type));
_biasLearningRateAnnealer = LearningRateAnnealerFactory.Produce(type);
Weights = new double[depth, size, size];
Gradient = new double[depth, size, size];
}
public Neuron(
IActivator activator,
IWeightInitializer weightInitializer,
int numberOfConnections,
LearningRateAnnealerType lrat)
{
Weights = new double[numberOfConnections];
_learningRateAnnealers = new ILearningRateAnnealer[numberOfConnections];
_learningRateAnnealers.ForEach((q, i) => _learningRateAnnealers[i] = LearningRateAnnealerFactory.Produce(lrat));
_biasLearningRateAnnealer = LearningRateAnnealerFactory.Produce(lrat);
double magnitude = 1 / Math.Sqrt(numberOfConnections);
Weights.ForEach((q, i) => Weights[i] = weightInitializer.GenerateRandom(magnitude));
_activator = activator;
}
