/// <summary>
/// Creates an instance of Unsuervised Hebian net with specified number
/// of neurons in input layer and output layer, and transfer function
/// </summary>
/// <param name="inputNeuronsNum">
/// number of neurons in input layer </param>
/// <param name="outputNeuronsNum">
/// number of neurons in output layer </param>
/// <param name="transferFunctionType">
/// transfer function type </param>
private void createNetwork(int inputNeuronsNum, int outputNeuronsNum, TransferFunctionType transferFunctionType)
{
// init neuron properties
NeuronProperties neuronProperties = new NeuronProperties();
// neuronProperties.setProperty("bias", new Double(-Math
// .abs(Math.random() - 0.5))); // Hebbian network cann not work
// without bias
neuronProperties.setProperty("transferFunction", transferFunctionType.ToString());
neuronProperties.setProperty("transferFunction.slope", 1);
// set network type code
this.NetworkType = NeuralNetworkType.UNSUPERVISED_HEBBIAN_NET;
// createLayer input layer
Layer inputLayer = LayerFactory.createLayer(inputNeuronsNum, neuronProperties);
this.addLayer(inputLayer);
// createLayer output layer
Layer outputLayer = LayerFactory.createLayer(outputNeuronsNum, neuronProperties);
this.addLayer(outputLayer);
// createLayer full conectivity between input and output layer
ConnectionFactory.fullConnect(inputLayer, outputLayer);
// set input and output cells for this network
NeuralNetworkFactory.DefaultIO = this;
// set appropriate learning rule for this network
this.LearningRule = new UnsupervisedHebbianLearning();
//this.setLearningRule(new OjaLearning(this));
}
/// <summary>
/// Creates an instance of Supervised Hebbian Network with specified number
/// of neurons in input layer, output layer and transfer function
/// </summary>
/// <param name="inputNeuronsNum">
/// number of neurons in input layer </param>
/// <param name="outputNeuronsNum">
/// number of neurons in output layer </param>
/// <param name="transferFunctionType">
/// transfer function type </param>
private void createNetwork(int inputNeuronsNum, int outputNeuronsNum, TransferFunctionType transferFunctionType)
{
// init neuron properties
NeuronProperties neuronProperties = new NeuronProperties();
neuronProperties.setProperty("transferFunction", transferFunctionType.ToString());
neuronProperties.setProperty("transferFunction.slope", 1);
neuronProperties.setProperty("transferFunction.yHigh", 1);
neuronProperties.setProperty("transferFunction.xHigh", 1);
neuronProperties.setProperty("transferFunction.yLow", -1);
neuronProperties.setProperty("transferFunction.xLow", -1);
// set network type code
this.NetworkType = NeuralNetworkType.SUPERVISED_HEBBIAN_NET;
// createLayer input layer
Layer inputLayer = LayerFactory.createLayer(inputNeuronsNum, neuronProperties);
this.addLayer(inputLayer);
// createLayer output layer
Layer outputLayer = LayerFactory.createLayer(outputNeuronsNum, neuronProperties);
this.addLayer(outputLayer);
// createLayer full conectivity between input and output layer
ConnectionFactory.fullConnect(inputLayer, outputLayer);
// set input and output cells for this network
NeuralNetworkFactory.DefaultIO = this;
// set appropriate learning rule for this network
this.LearningRule = new SupervisedHebbianLearning();
}
/// <summary>
/// Creates an instance of Unsuervised Hebian net with specified number
/// of neurons in input layer and output layer, and transfer function
/// </summary>
/// <param name="inputNeuronsNum">
/// number of neurons in input layer </param>
/// <param name="outputNeuronsNum">
/// number of neurons in output layer </param>
/// <param name="transferFunctionType">
/// transfer function type id </param>
public UnsupervisedHebbianNetwork(int inputNeuronsNum, int outputNeuronsNum, TransferFunctionType transferFunctionType)
{
this.createNetwork(inputNeuronsNum, outputNeuronsNum, transferFunctionType);
}
