// Линейный энкодер
private void creatLin_Click(object sender, EventArgs e)
{
lin = true;
nnw = new NNW();
nnw.AddNewLayer(new Shape(n), new FeedForwardLayer(h));
nnw.AddNewLayer(new FeedForwardLayer(n));
CreateMeneger();
}
public ComplexNet()
{
InitializeComponent();
t = new Vector(n);
double dt = 1.0 / n;
for (int i = 1; i < n; i++)
{
t[i] = t[i - 1] + dt;
}
NNW.AddNewLayer(new Shape(n), new ComplexFeedForwardLayer(20, new CSigmoidUnit()));
NNW.AddNewLayer(new ComplexFeedForwardLayer(outp, new CLinearUnit()));
}
public ImitComplex()
{
InitializeComponent();
t = new Vector(n);
double dt = 1.0 / n;
for (int i = 1; i < n; i++)
{
t[i] = t[i - 1] + dt;
}
NNW.AddNewLayer(new Shape(n), new FeedForwardLayer(100, new ReLU(0.1)));
NNW.AddNewLayer(new ReShape(new Shape(10, 1, 2))); // Разделение на реальную и мнимую часть
NNW.AddNewLayer(new BatchReNormalization());
NNW.AddNewLayer(new FeedComplexLayer(1000, new EliotSigUnit())); // Комплексный слой
NNW.AddNewLayer(new DropOut(0.85));
NNW.AddNewLayer(new Flatten()); // Соединение реальной и мнимой части
NNW.AddNewLayer(new FeedForwardLayer(outp, new SigmoidWithBCE()));
Console.WriteLine(NNW);
}
//Сверточный энкодер
private void creatConv_Click(object sender, EventArgs e)
{
lin = false;
nnw = new NNW();
nnw.AddNewLayer(new Shape(n), new Conv1D(3, 8, new ReLU(0.1)));
nnw.AddNewLayer(new MaxPool1D());
nnw.AddNewLayer(new Conv1D(3, 16, new ReLU(0.1)));
nnw.AddNewLayer(new MaxPool1D());
nnw.AddNewLayer(new Conv1D(3, 16, new ReLU(0.1)));
nnw.AddNewLayer(new MaxPool1D());
nnw.AddNewLayer(new Flatten());
nnw.AddNewLayer(new FeedForwardLayer(h));
nnw.AddNewLayer(new FeedForwardLayer(64, new ReLU(0.1)));
nnw.AddNewLayer(new UpSampling1D());
nnw.AddNewLayer(new Conv1D(3, 32, new ReLU(0.1))
{
IsSame = true
});
nnw.AddNewLayer(new UpSampling1D());
nnw.AddNewLayer(new Conv1D(3, 16, new ReLU(0.1))
{
IsSame = true
});
nnw.AddNewLayer(new UpSampling1D());
nnw.AddNewLayer(new Conv1D(3, 1, new LinearUnit())
{
IsSame = true
});
CreateMeneger();
}