public void Configure()
{
this.fInputLayer = (TNeuralLayer) new TInputNeuralLayer(this.fNInput, true);
TNeuralLayer Layer = (TNeuralLayer) new THiddenNeuralLayer(this.kB5uny9D9);
Layer.Connect(this.fInputLayer);
this.rCHgEckPw = new ArrayList();
this.HnCyxyTcM = 1;
this.rCHgEckPw.Add((object)Layer);
this.fOutputLayer = (TNeuralLayer) new TOutputNeuralLayer(this.fNOutput, this.wAeTg5Tjg);
this.fOutputLayer.Connect(Layer);
this.fOutput = new double[this.fNOutput];
this.cGqCj2YUM = new double[this.fNOutput];
this.fMaxNX = Math.Max(this.fNInput + 1, this.fNOutput);
this.fMaxNX = Math.Max(this.fMaxNX, this.kB5uny9D9 + 1);
this.fMaxNY = 3;
this.fNPattern = 0;
this.wm8s050QY = 0.0;
this.MSg9cpEpW = 0.0;
this.V8laR9xb7 = new Graph();
this.V8laR9xb7.Title = "title";
this.V8laR9xb7.LineColor = Color.Red;
this.XOwvCEen2 = new Graph();
this.XOwvCEen2.Title = "title";
this.XOwvCEen2.LineColor = Color.Blue;
this.x1tDaZE2v = false;
}
public void Disconnect(TNeuralLayer Layer)
{
foreach (TNeuron tneuron in this.fNeuron)
{
foreach (TNeuron Neuron in Layer.fNeuron)
tneuron.Disconnect(Neuron);
}
}
public void Disconnect(TNeuralLayer Layer)
{
foreach (TNeuron tneuron in this.fNeuron)
{
foreach (TNeuron Neuron in Layer.fNeuron)
{
tneuron.Disconnect(Neuron);
}
}
}
public void AddHiddenLayer(int NHidden)
{
TNeuralLayer Layer1 = (TNeuralLayer)this.rCHgEckPw[this.rCHgEckPw.Count - 1];
TNeuralLayer Layer2 = (TNeuralLayer) new THiddenNeuralLayer(NHidden);
this.fOutputLayer.Disconnect(Layer1);
this.fOutputLayer.Connect(Layer2);
Layer2.Connect(Layer1);
this.rCHgEckPw.Add((object)Layer2);
++this.HnCyxyTcM;
this.kB5uny9D9 += NHidden;
this.fMaxNX = Math.Max(this.fMaxNX, NHidden + 1);
TPerceptron tperceptron = this;
int num = tperceptron.fMaxNY + 1;
tperceptron.fMaxNY = num;
}