/// <summary>
/// Generate the RSOM network.
/// </summary>
/// <returns>The neural network.</returns>
public BasicNetwork Generate()
{
ILayer output = new BasicLayer(new ActivationLinear(), false,
this.outputNeurons);
ILayer input = new BasicLayer(new ActivationLinear(), false,
this.inputNeurons);
BasicNetwork network = new BasicNetwork();
ILayer context = new ContextLayer(this.outputNeurons);
network.AddLayer(input);
network.AddLayer(output);
output.AddNext(context, SynapseType.OneToOne);
context.AddNext(input);
int y = PatternConst.START_Y;
input.X = PatternConst.START_X;
input.Y = y;
context.X = PatternConst.INDENT_X;
context.Y = y;
y += PatternConst.INC_Y;
output.X = PatternConst.START_X;
output.Y = y;
network.Structure.FinalizeStructure();
network.Reset();
return(network);
}
/// <summary>
/// Generate the Hopfield neural network.
/// </summary>
/// <returns>The generated network.</returns>
public BasicNetwork Generate()
{
ILayer layer = new BasicLayer(new ActivationBiPolar(), false,
this.neuronCount);
BasicNetwork result = new BasicNetwork(new HopfieldLogic());
result.AddLayer(layer);
layer.AddNext(layer);
layer.X = PatternConst.START_X;
layer.Y = PatternConst.START_Y;
result.Structure.FinalizeStructure();
result.Reset();
return(result);
}
/// <summary>
/// Generate the network.
/// </summary>
/// <returns>The generated network.</returns>
public BasicNetwork Generate()
{
ILayer layer = new BasicLayer(new ActivationBiPolar(), true,
this.neuronCount);
BasicNetwork result = new BasicNetwork(new BoltzmannLogic());
result.SetProperty(BoltzmannLogic.PROPERTY_ANNEAL_CYCLES, this.annealCycles);
result.SetProperty(BoltzmannLogic.PROPERTY_RUN_CYCLES, this.runCycles);
result.SetProperty(BoltzmannLogic.PROPERTY_TEMPERATURE, this.temperature);
result.AddLayer(layer);
layer.AddNext(layer);
layer.X = PatternConst.START_X;
layer.Y = PatternConst.START_Y;
result.Structure.FinalizeStructure();
result.Reset();
return(result);
}
/// <summary>
/// Generate a Jordan neural network.
/// </summary>
/// <returns>A Jordan neural network.</returns>
public BasicNetwork Generate()
{
// construct an Jordan type network
ILayer input = new BasicLayer(this.activation, false,
this.inputNeurons);
ILayer hidden = new BasicLayer(this.activation, true,
this.hiddenNeurons);
ILayer output = new BasicLayer(this.activation, true,
this.outputNeurons);
ILayer context = new ContextLayer(this.outputNeurons);
BasicNetwork network = new BasicNetwork();
network.AddLayer(input);
network.AddLayer(hidden);
network.AddLayer(output);
output.AddNext(context, SynapseType.OneToOne);
context.AddNext(hidden);
int y = PatternConst.START_Y;
input.X = PatternConst.START_X;
input.Y = y;
y += PatternConst.INC_Y;
hidden.X = PatternConst.START_X;
hidden.Y = y;
context.X = PatternConst.INDENT_X;
context.Y = y;
y += PatternConst.INC_Y;
output.X = PatternConst.START_X;
output.Y = y;
network.Structure.FinalizeStructure();
network.Reset();
return(network);
}