private double[] GetOutputs()
{
Layer lastLayer = layers[layers.Length - 1];
double[] outputs = new double[lastLayer.Neurons.Length];
Array.ForEach(NetMath.Range(lastLayer.Neurons.Length), i => outputs[i] = lastLayer.Neurons[i].Val);
return(outputs);
}
public void Propagate()
{
for (int i = 1; i < layers.Length; i++)
{
double[] prevLayerValues = new double[layers[i - 1].Neurons.Length];
Array.ForEach(NetMath.Range(layers[i - 1].Neurons.Length), j => prevLayerValues[j] = layers[i - 1].Neurons[j].Val);
for (int j = 0; j < layers[i].Neurons.Length; j++)
{
double dotSum = NetMath.DotProduct(prevLayerValues, layers[i].Neurons[j].Weights);
double activated = Sigmoid(dotSum + layers[i].Neurons[j].Bias);
layers[i].Neurons[j].Val = activated;
}
}
}
private void SetInputs(double[] inputs)
{
Array.ForEach(NetMath.Range(inputs.Length), i => layers[0].Neurons[i].Val = inputs[i]);
}
