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(); }