public LinearSystemTask()
{
Neuron.DefaultActivationFunction = ActivationFunction.LINEAR;
NeuronGroups.Add(new NeuronGroup(2));
NeuronGroups.Add(new NeuronGroup(2));
InputsCount = 2;
}
public RBFNeuralNet()
{
Inputs.Add(new NeuronInput("Параметр № " + (1).ToString()));
Neuron.DefaultActivationFunction = ActivationFunction.RADIAL_VEC;
NeuronGroups.Add(new NeuronGroup(2));
Neuron.DefaultActivationFunction = ActivationFunction.LINEAR;
NeuronGroups.Add(new NeuronGroup(1));
SetSinapses();
initCenters();
}
public KohonenNeuronNet()
{
Neuron.DefaultActivationFunction = ActivationFunction.RADIAL;
for (int i = 0; i < 2; i++)
{
Inputs.Add(new NeuronInput("Параметр № " + (i + 1).ToString()));
}
NeuronGroups.Add(new NeuronGroup(3));
SetSinapses();
}
public int InitTask(Matrix A, Matrix B)
{
NeuronGroups.Clear();
NeuronGroups.Add(new NeuronGroup(A.Width));
NeuronGroups.Add(new NeuronGroup(A.Height));
InputsCount = A.Height;
OutputsCount = A.Height;
InitNet(A, B);
return(1);
}
public HopfieldNeuronNet()
{
Neuron.DefaultActivationFunction = ActivationFunction.LIMIT;
for (int i = 0; i < 3; i++)
{
Inputs.Add(new NeuronInput("Параметр № " + (i + 1).ToString()));
}
NeuronGroups.Add(new NeuronGroup(3));
SetSinapses();
}
public LinearNeuronNet()
{
Neuron.DefaultActivationFunction = ActivationFunction.LOGISTIC;
for (int i = 0; i < 2; i++)
{
Inputs.Add(new NeuronInput("Параметр № " + (i + 1).ToString()));
}
NeuronGroups.Add(new NeuronGroup(2));
NeuronGroups.Add(new NeuronGroup(1));
SetSinapses();
}
