static void Main(string[] args)
{
var neuron1 = new Neuron();
var neuron2 = new Neuron();
neuron1.ConnectTo(neuron2);
var layer1 = new NeuronLayer();
var layer2 = new NeuronLayer();
neuron1.ConnectTo(layer1);
layer1.ConnectTo(layer2);
Console.WriteLine("Hello World!");
}
static void Main(string[] args)
{
var neuron1 = new Neuron();
var neuron2 = new Neuron();
neuron1.ConnectTo(neuron2);
var neuronLayer1 = new NeuronLayer();
var neuronLayer2 = new NeuronLayer();
neuron1.ConnectTo(neuronLayer1);
neuronLayer1.ConnectTo(neuronLayer2);
neuronLayer2.ConnectTo(neuron2);
Console.ReadLine();
}
public NeuralNetwork(int inputsCount, int outputCount, int layersCount, int layerSize)
{
_lastLayer = new NeuronLayer(outputCount);
_lastLayer.AddInputs(layerSize);
_inputsCount = inputsCount;
var firstLayer = new NeuronLayer(layerSize);
firstLayer.AddInputs(inputsCount);
_layers.Add(firstLayer);
for (var i = 1; i < layersCount; i++)
{
var nl = new NeuronLayer(layerSize);
nl.AddInputs(layerSize);
_layers.Add(nl);
}
}
NeuronLayer LoadLayer(string layerData)
{
string[] neuronsData = System.Text.RegularExpressions.Regex.Split(layerData, "#Neuron");
List <Neuron> neurons = new List <Neuron>();
foreach (string neuronData in neuronsData)
{
if (neuronData.Length > 5)
{
neurons.Add(LoadNeuron(neuronData));
}
}
NeuronLayer layer = new NeuronLayer();
layer.neuronCount = neurons.Count;
layer.neurons = neurons.ToArray();
return(layer);
}
/// <summary>
/// Creates the network
/// </summary>
internal void CreateNet()
{
//Sum the weights and inputs
layers = new NeuronLayer[numHiddenLayers + 1];
if (numHiddenLayers > 0)
{
layers[0] = new NeuronLayer(numNeuronHiddenLayer, numInputs);
for (int k = 1; k < numHiddenLayers; k++)
{
layers[k] = new NeuronLayer(numNeuronHiddenLayer, numNeuronHiddenLayer);
}
layers[numHiddenLayers] = new NeuronLayer(numOutputs, numNeuronHiddenLayer);
}
else
{
layers[0] = new NeuronLayer(numOutputs, numInputs);
}
}
