org.neuroph.util

Class NeuralNetworkFactory

java.lang.Object

org.neuroph.util.NeuralNetworkFactory

public class NeuralNetworkFactory
extends java.lang.Object

Provides methods to create various neural networks.

Constructor Summary

Constructors

Constructor and Description
NeuralNetworkFactory()

Method Summary

Modifier and Type	Method and Description
static Adaline	createAdaline(int inputsCount) Creates and returns a new instance of Adaline network
static BAM	createBam(int inputNeuronsCount, int outputNeuronsCount) Creates and returns a new instance of BAM network
static CompetitiveNetwork	createCompetitiveNetwork(int inputNeuronsCount, int outputNeuronsCount) Creates and returns a new instance of competitive network
static Hopfield	createHopfield(int neuronsCount) Creates and returns a new instance of Hopfield network
static Instar	createInstar(int inputNeuronsCount) Creates and returns a new instance of Instar network
static Kohonen	createKohonen(int inputNeuronsCount, int outputNeuronsCount) Creates and returns a new instance of Kohonen network
static MaxNet	createMaxNet(int neuronsCount) Creates and returns a new instance of Max Net network
static MultiLayerPerceptron	createMLPerceptron(java.lang.String layersStr, TransferFunctionType transferFunctionType) Creates and returns a new instance of Multi Layer Perceptron
static MultiLayerPerceptron	createMLPerceptron(java.lang.String layersStr, TransferFunctionType transferFunctionType, java.lang.Class learningRule, boolean useBias, boolean connectIO) Creates and returns a new instance of Multi Layer Perceptron
static Outstar	createOutstar(int outputNeuronsCount) Creates and returns a new instance of Outstar network
static Perceptron	createPerceptron(int inputNeuronsCount, int outputNeuronsCount, TransferFunctionType transferFunctionType) Creates and returns a new instance of Perceptron network
static Perceptron	createPerceptron(int inputNeuronsCount, int outputNeuronsCount, TransferFunctionType transferFunctionType, java.lang.Class learningRule) Creates and returns a new instance of Perceptron network
static RBFNetwork	createRbfNetwork(int inputNeuronsCount, int rbfNeuronsCount, int outputNeuronsCount) Creates and returns a new instance of RBF network
static SupervisedHebbianNetwork	createSupervisedHebbian(int inputNeuronsCount, int outputNeuronsCount, TransferFunctionType transferFunctionType) Creates and returns a new instance of Hebbian network
static UnsupervisedHebbianNetwork	createUnsupervisedHebbian(int inputNeuronsCount, int outputNeuronsCount, TransferFunctionType transferFunctionType) Creates and returns a new instance of Unsupervised Hebbian Network
static void	setDefaultIO(NeuralNetwork nnet) Sets default input and output neurons for network (first layer as input, last as output)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

NeuralNetworkFactory

public NeuralNetworkFactory()

Method Detail

createAdaline

public static Adaline createAdaline(int inputsCount)

Creates and returns a new instance of Adaline network

Parameters:

inputsCount - number of inputs of Adaline network

Returns:

instance of Adaline network

createPerceptron

public static Perceptron createPerceptron(int inputNeuronsCount,
                                          int outputNeuronsCount,
                                          TransferFunctionType transferFunctionType)

Creates and returns a new instance of Perceptron network

Parameters:

inputNeuronsCount - number of neurons in input layer

outputNeuronsCount - number of neurons in output layer

transferFunctionType - type of transfer function to use

Returns:

instance of Perceptron network

createPerceptron

public static Perceptron createPerceptron(int inputNeuronsCount,
                                          int outputNeuronsCount,
                                          TransferFunctionType transferFunctionType,
                                          java.lang.Class learningRule)

Creates and returns a new instance of Perceptron network

Parameters:

inputNeuronsCount - number of neurons in input layer

outputNeuronsCount - number of neurons in output layer

transferFunctionType - type of transfer function to use

learningRule - learning rule class

Returns:

instance of Perceptron network

createMLPerceptron

public static MultiLayerPerceptron createMLPerceptron(java.lang.String layersStr,
                                                      TransferFunctionType transferFunctionType)

Creates and returns a new instance of Multi Layer Perceptron

Parameters:

layersStr - space separated number of neurons in layers

transferFunctionType - transfer function type for neurons

Returns:

instance of Multi Layer Perceptron

createMLPerceptron

public static MultiLayerPerceptron createMLPerceptron(java.lang.String layersStr,
                                                      TransferFunctionType transferFunctionType,
                                                      java.lang.Class learningRule,
                                                      boolean useBias,
                                                      boolean connectIO)

Creates and returns a new instance of Multi Layer Perceptron

Parameters:

layersStr - space separated number of neurons in layers

transferFunctionType - transfer function type for neurons

Returns:

instance of Multi Layer Perceptron

createHopfield

public static Hopfield createHopfield(int neuronsCount)

Creates and returns a new instance of Hopfield network

Parameters:

neuronsCount - number of neurons in Hopfield network

Returns:

instance of Hopfield network

createBam

public static BAM createBam(int inputNeuronsCount,
                            int outputNeuronsCount)

Creates and returns a new instance of BAM network

Parameters:

inputNeuronsCount - number of input neurons

outputNeuronsCount - number of output neurons

Returns:

instance of BAM network

createKohonen

public static Kohonen createKohonen(int inputNeuronsCount,
                                    int outputNeuronsCount)

Creates and returns a new instance of Kohonen network

Parameters:

inputNeuronsCount - number of input neurons

outputNeuronsCount - number of output neurons

Returns:

instance of Kohonen network

createSupervisedHebbian

public static SupervisedHebbianNetwork createSupervisedHebbian(int inputNeuronsCount,
                                                               int outputNeuronsCount,
                                                               TransferFunctionType transferFunctionType)

Creates and returns a new instance of Hebbian network

Parameters:

inputNeuronsCount - number of neurons in input layer

outputNeuronsCount - number of neurons in output layer

transferFunctionType - neuron's transfer function type

Returns:

instance of Hebbian network

createUnsupervisedHebbian

public static UnsupervisedHebbianNetwork createUnsupervisedHebbian(int inputNeuronsCount,
                                                                   int outputNeuronsCount,
                                                                   TransferFunctionType transferFunctionType)

Creates and returns a new instance of Unsupervised Hebbian Network

Parameters:

inputNeuronsCount - number of neurons in input layer

outputNeuronsCount - number of neurons in output layer

transferFunctionType - neuron's transfer function type

Returns:

instance of Unsupervised Hebbian Network

createMaxNet

public static MaxNet createMaxNet(int neuronsCount)

Creates and returns a new instance of Max Net network

Parameters:

neuronsCount - number of neurons (same num in input and output layer)

Returns:

instance of Max Net network

createInstar

public static Instar createInstar(int inputNeuronsCount)

Creates and returns a new instance of Instar network

Parameters:

inputNeuronsCount - umber of input neurons

Returns:

instance of Instar network

createOutstar

public static Outstar createOutstar(int outputNeuronsCount)

Creates and returns a new instance of Outstar network

Parameters:

outputNeuronsCount - number of output neurons

Returns:

instance of Outstar network

createCompetitiveNetwork

public static CompetitiveNetwork createCompetitiveNetwork(int inputNeuronsCount,
                                                          int outputNeuronsCount)

Creates and returns a new instance of competitive network

Parameters:

inputNeuronsCount - number of neurons in input layer

outputNeuronsCount - number of neurons in output layer

Returns:

instance of CompetitiveNetwork

createRbfNetwork

public static RBFNetwork createRbfNetwork(int inputNeuronsCount,
                                          int rbfNeuronsCount,
                                          int outputNeuronsCount)

Creates and returns a new instance of RBF network

Parameters:

inputNeuronsCount - number of neurons in input layer

rbfNeuronsCount - number of neurons in RBF layer

outputNeuronsCount - number of neurons in output layer

Returns:

instance of RBF network

setDefaultIO

public static void setDefaultIO(NeuralNetwork nnet)

Sets default input and output neurons for network (first layer as input, last as output)