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); } }