public RecurrentNetwork(int inputNeuronsCount, int outputNeuronsCount, int hiddenLayersCount, int hiddenNeuronsCount)
{
//Initizating input layer
_inputLayer = new Layer(inputNeuronsCount, new LinearFunction(), null, null);
Layers.Add(_inputLayer);
//Initizating hidden layers
var hiddenLayers = new List<Layer>();
for (var i = 0; i < hiddenLayersCount; i++)
{
var hiddenLayer = new Layer(hiddenNeuronsCount, new SigmoidFunction(), Layers.Last(), null);
Layers.Last().SetOutputLayer(hiddenLayer);
hiddenLayers.Add(hiddenLayer);
}
Layers.AddRange(hiddenLayers);
//Initizating output layer
_outputLayer = new Layer(outputNeuronsCount, new SigmoidFunction(), Layers.Last(), null);
Layers.Last().SetOutputLayer(_outputLayer);
Layers.Add(_outputLayer);
//Initizating recurrent layer
_recurrentLayer = new Layer(0, new LinearFunction(), null, hiddenLayers[0]);
hiddenLayers[0].SetRecurrentLayer(_recurrentLayer);
Layers.Add(_recurrentLayer);
}
public Layer(int neuronCount, IActivationFunction activationFunction, Layer inputLayer, Layer outputLayer, Layer recurrentLayer = null)
{
NeuronCount = neuronCount;
InputLayer = inputLayer;
OutputLayer = outputLayer;
RecurrentLayer = recurrentLayer;
ActivationFunction = activationFunction;
UpdateMarkers();
for (var i = 0; i < NeuronCount; i++)
Neurons.Add(new Neuron(this));
}
public void SetRecurrentLayer(Layer recurrentLayer)
{
RecurrentLayer = recurrentLayer;
RecurrentLayer.UpdateMarkers();
}
public void SetOutputLayer(Layer outputLayer)
{
OutputLayer = outputLayer;
UpdateMarkers();
}
public void SetInputLayer(Layer inputLayer)
{
InputLayer = inputLayer;
UpdateMarkers();
}
public Neuron(Layer parent)
{
_parent = parent;
}
