public ART1 BuildNetwork(int inputSize, float vigilance = 0.5f, int initialClusterCount = 0)
{
Contract.Requires<ArgumentOutOfRangeException>(0 < inputSize, "Size of the input vector must be positive.");
Contract.Requires<ArgumentOutOfRangeException>(0f < vigilance && vigilance < 1f, "Vigilance parameter must be in (0,1) range.");
Contract.Requires<ArgumentOutOfRangeException>(0 <= initialClusterCount, "Initial cluster count must be nonnegative.");
InputNeuronFactory inputNeuronFactory = new InputNeuronFactory();
InputLayerBuilder inputLayerBuilder = new InputLayerBuilder(inputNeuronFactory);
InputLayer inputLayer = inputLayerBuilder.Build(inputSize);
ConnectionFactory connectionFactory = new ConnectionFactory();
OutputNeuronFactory outputNeuronFactory = new OutputNeuronFactory(inputLayer, connectionFactory);
OutputLayerBuilder outputLayerBuilder = new OutputLayerBuilder(outputNeuronFactory);
OutputLayer outputLayer = outputLayerBuilder.Build(initialClusterCount);
OrientingSubsystem orientingSubsystem = new OrientingSubsystem(inputLayer, outputLayer);
orientingSubsystem.Vigilance = vigilance;
AttentionalSubsystem attentionalSubsystem = new AttentionalSubsystem(orientingSubsystem, inputLayer, outputLayer);
ART1 network = new ART1(attentionalSubsystem);
return network;
}
public ART1PictogramClassifier(ART1 art1Network)
{
this.art1Network = art1Network;
}
public void Renew(int width, int height, float vigilance)
{
network = ART1Builder.Instance.BuildNetwork(width * height, vigilance);
patternInputProcessor.Renew(width, height);
}
