public static void Connect(Perceptron main, Perceptron perceptron, Synapse synapse)
{
main.perceptrons_to.Add(perceptron);
main.synapses_to.Add(synapse);
perceptron.perceptrons_from.Add(main);
perceptron.synapses_from.Add(synapse);
perceptron.index_in_other_perceptrons.Add(perceptron.perceptrons_from.Count - 1);
}
public void BackPropagation(float lr, float mr)
{
int len = perceptrons_to.Count;
for (int i = 0; i < len; i++)
{
Perceptron perc = perceptrons_to[i];
Synapse syn = synapses_to[i];
syn.error = (lr * activation() * perc.error) + (mr * syn.error);
syn.x += syn.error;
}
}
public void FeedForward()
{
if (type == PerceptronType.Type.hidden || type == PerceptronType.Type.output)
{
state = 0f;
int len = perceptrons_from.Count;
for (int i = 0; i < len; i++)
{
Perceptron perc = perceptrons_from[index_in_other_perceptrons[i]];
Synapse syn = synapses_from[index_in_other_perceptrons[i]];
state += perc.activation() * syn.x;
}
}
}
public void BlackError()
{
var x = activation();
var derivate = activation(true);
if (type == PerceptronType.Type.output)
{
error = (desired - x) * derivate;
}
else
{
int len = perceptrons_to.Count;
float er = 0f;
for (int i = 0; i < len; i++)
{
Perceptron perc = perceptrons_to[i];
Synapse syn = synapses_to[i];
er += perc.error * syn.x;
}
error = derivate * er;
}
}