//Sends the inputs once through the network public void Train(params double[] inputs) { int i = 0; InputLayer.ForEach(a => a.Value = inputs[i++]); //Assign input data to input-neurons HiddenLayer.ForEach(a => a.Calc_Value()); //Hidden Calc OutputLayer.ForEach(a => a.Calc_Value()); //Outuput Calc }
//Obliczenie wartości wyjściowej sieci neuronowej dla pojedyńczego elementu private void ForwardPropagate(double[] inputs) { var i = 0; InputLayer.ForEach(a => a.Value = inputs[i++]); HiddenLayers.ForEach(a => a.ForEach(b => b.CalculateValue())); OutputLayer.ForEach(a => a.CalculateValue()); }
public void updateWeights(double[] weights) { // Set each weight in the neural net to its gene representation int i = 0; InputLayer.ForEach(neuron => neuron.OutputSynapses.ForEach(synapse => synapse.Weight = weights[i++])); HiddenLayer.ForEach(neuron => neuron.OutputSynapses.ForEach(synapse => synapse.Weight = weights[i++])); }
private void ForwardPropagate(params double[] inputs) { int i = 0; InputLayer.ForEach(a => a.Value = inputs[i++]); HiddenLayers.ForEach(a => a.AsParallel().ForAll(b => b.CalculateValue())); OutputLayer.AsParallel().ForAll(a => a.CalculateValue()); }
public void ForwardPropagate(params double[] inputs) { var i = 0; InputLayer.ForEach(a => a.Value = inputs[i++]); HiddenLayer.ForEach(a => a.CalculateValue()); OutputLayer.ForEach(a => a.CalculateValue()); }
public void Train(params double[] inputs) { int i = 0; InputLayer.ForEach(a => a.Value = inputs[i++]); HiddenLayer.ForEach(a => a.CalculateValue()); OutputLayer.ForEach(a => a.CalculateValue()); }
/// <summary> /// Feed the input to the network and propagate forwards /// </summary> /// <param name="inputs">the feeded input data</param> private void ForwardPropagate(params double[] inputs) { int i = 0; InputLayer.ForEach(p => p.Value = inputs[i++]); HiddenLayer.ForEach(p => p.CalculateValue()); OutputLayer.ForEach(p => p.CalculateValue()); }
private void ForwardPropagate(params double[] inputs) { var i = 0; InputLayer.ForEach(a => a.Value = inputs[i++]); foreach (var layer in HiddenLayers) { layer.ForEach(a => a.CalculateValue()); } OutputLayer.ForEach(a => a.CalculateValue()); }
private void ForwardPropagate(params double[] inputs) { int i = 0; InputLayer.ForEach(a => a.Value = inputs[i++]); foreach (List <Neuron> Layer in HiddenLayers) { Layer.ForEach(a => a.CalculateValue()); } OutputLayer.ForEach(a => a.CalculateValue()); }
private void ForwardPropagate(params float[] inputs) { int i = 0; InputLayer.ForEach(neuron => neuron.Value = inputs[i++]); foreach (var layer in HiddenLayer) { layer.ForEach(neuron => neuron.CalculateValue()); } OutputLayer.ForEach(neuron => neuron.CalculateValue()); }
//前向演进 public void ForwardPropagate(params double[] inputs) { var i = 0; InputLayer.ForEach(a => a.OutputValue = inputs[i++]); //HiddenLayers.ForEach(a => a.ForEach(b => b.CalculateValue())); //OutputLayer.ForEach(a => a.CalculateValue()); foreach (List <Neuron> HiddenLayer in HiddenLayers) { Parallel.ForEach(HiddenLayer, a => { a.CalculateValue(); }); } Parallel.ForEach(OutputLayer, a => { a.CalculateValue(); }); }