Package gov.nih.mipav.model.algorithms

Class Backpropagation.NeuralNetwork

java.lang.Object

gov.nih.mipav.model.algorithms.Backpropagation.NeuralNetwork

Enclosing class:

Backpropagation

public class Backpropagation.NeuralNetwork
extends java.lang.Object

Field Summary

Fields

Modifier and Type	Field	Description
private java.util.ArrayList<Backpropagation.Neuron[]>	hiddenLayers
private java.util.ArrayList<Backpropagation.Neuron>	inputLayer
private java.util.ArrayList<java.lang.Double[]>	inputs
private double	learningRate
private double	momentum
private java.util.ArrayList<java.lang.Double>	outputKinds
private java.util.ArrayList<Backpropagation.Neuron>	outputLayer
private java.util.Random	rand

Constructor Summary

Constructors

Constructor	Description
NeuralNetwork(java.util.ArrayList<java.lang.Double[]> inputs, java.util.ArrayList<java.lang.Double> outputKinds, java.lang.String hidden, double momentum, double learningRate, double threshold, double minRange, double maxRange)

Method Summary

Modifier and Type	Method	Description
private void	activate()
private void	applyBackpropagation(java.lang.Double[] expectedOutput)
private java.lang.Double[]	getOutput()
int[]	getOutputKind(java.util.ArrayList<java.lang.Double[]> inputs, int maxSteps, double minError)
private java.lang.Double	getRandomNumber(java.lang.Double minRange, java.lang.Double maxRange)
private void	printAllWeights()
private void	printWeights(Backpropagation.Neuron n)
java.lang.String	run(int maxSteps, double minError)
private void	setInput(java.lang.Double[] inputs)
java.lang.String	test(java.util.ArrayList<java.lang.Double[]> inputs, int maxSteps, double minError)

Methods inherited from class java.lang.Object

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

Field Detail

rand

private final java.util.Random rand

inputLayer

private final java.util.ArrayList<Backpropagation.Neuron> inputLayer

hiddenLayers

private final java.util.ArrayList<Backpropagation.Neuron[]> hiddenLayers

outputLayer

private final java.util.ArrayList<Backpropagation.Neuron> outputLayer

momentum

private double momentum

learningRate

private double learningRate

inputs

private java.util.ArrayList<java.lang.Double[]> inputs

outputKinds

private java.util.ArrayList<java.lang.Double> outputKinds

Constructor Detail

NeuralNetwork

public NeuralNetwork(java.util.ArrayList<java.lang.Double[]> inputs,
                     java.util.ArrayList<java.lang.Double> outputKinds,
                     java.lang.String hidden,
                     double momentum,
                     double learningRate,
                     double threshold,
                     double minRange,
                     double maxRange)

Method Detail

getRandomNumber

private java.lang.Double getRandomNumber(java.lang.Double minRange,
                                         java.lang.Double maxRange)

setInput

private void setInput(java.lang.Double[] inputs)

getOutput

private java.lang.Double[] getOutput()

activate

private void activate()

applyBackpropagation

private void applyBackpropagation(java.lang.Double[] expectedOutput)

run

public java.lang.String run(int maxSteps,
                            double minError)

test

public java.lang.String test(java.util.ArrayList<java.lang.Double[]> inputs,
                             int maxSteps,
                             double minError)

getOutputKind

public int[] getOutputKind(java.util.ArrayList<java.lang.Double[]> inputs,
                           int maxSteps,
                           double minError)

printAllWeights

private void printAllWeights()

printWeights

private void printWeights(Backpropagation.Neuron n)