public Neuron(int numOutputs, int myIndex, ActivationFuntions activationFunctions = null)
{
ActiveFuns = activationFunctions ?? ActivationFuntions.Tanh;
_outputWeights = new Connection[numOutputs];
_myIndex = myIndex;
var random = new Random(0);
for (int i = 0; i < numOutputs; i++)
{
_outputWeights[i] = new Connection
{
Weight = random.NextDouble(),
}
}
;
}
public Net(int[] topology, ActivationFuntions activationFunctions = null)
{
_layers = new Layer[topology.Length];
for (int layerNum = 0; layerNum < topology.Length; ++layerNum)
{
_layers[layerNum] = new Layer();
int numOutputs = (layerNum == topology.Count() - 1)
? 0
: topology[layerNum + 1];
for (int i = 0; i <= topology[layerNum]; i++)
{
_layers[layerNum].Add(new Neuron(numOutputs, i, activationFunctions));
}
_layers[layerNum].Last().OutputVal = 1;
}
}
