org.neuroph.nnet.learning
Class DynamicBackPropagation

java.lang.Object
  java.util.Observable
      org.neuroph.core.learning.LearningRule
          org.neuroph.core.learning.IterativeLearning
              org.neuroph.core.learning.SupervisedLearning
                  org.neuroph.nnet.learning.LMS
                      org.neuroph.nnet.learning.SigmoidDeltaRule
                          org.neuroph.nnet.learning.BackPropagation
                              org.neuroph.nnet.learning.MomentumBackpropagation
                                  org.neuroph.nnet.learning.DynamicBackPropagation

All Implemented Interfaces:

java.io.Serializable, java.lang.Runnable

public class DynamicBackPropagation
extends MomentumBackpropagation

Backpropagation learning rule with momentum and dynamic learning rate

Author:

Zoran Sevarac

See Also:

Serialized Form

Field Summary

Fields inherited from class org.neuroph.nnet.learning.MomentumBackpropagation

momentum

Fields inherited from class org.neuroph.core.learning.SupervisedLearning

maxError, totalNetworkError

Fields inherited from class org.neuroph.core.learning.IterativeLearning

currentIteration, iterationsLimited, learningRate, maxIterations

Fields inherited from class org.neuroph.core.learning.LearningRule

neuralNetwork

Constructor Summary

DynamicBackPropagation()

DynamicBackPropagation(NeuralNetwork neuralNetwork)

Method Summary

protected void	adjustLearningRate()
protected void	adjustMomentum()
void	doLearningEpoch(TrainingSet trainingSet) This method implements basic logic for one learning epoch for the supervised learning algorithms.

Methods inherited from class org.neuroph.nnet.learning.MomentumBackpropagation

getMomentum, setMomentum, updateNeuronWeights

Methods inherited from class org.neuroph.nnet.learning.BackPropagation

updateNetworkWeights

Methods inherited from class org.neuroph.nnet.learning.SigmoidDeltaRule

adjustOutputNeurons

Methods inherited from class org.neuroph.nnet.learning.LMS

updateTotalNetworkError

Methods inherited from class org.neuroph.core.learning.SupervisedLearning

getPatternError, getTotalNetworkError, learn, learn, learnPattern, setMaxError

Methods inherited from class org.neuroph.core.learning.IterativeLearning

doOneLearningIteration, getCurrentIteration, getLearningRate, isPausedLearning, learn, learn, pause, resume, setLearningRate, setMaxIterations

Methods inherited from class org.neuroph.core.learning.LearningRule

getNeuralNetwork, getTrainingSet, isStopped, notifyChange, run, setNeuralNetwork, setTrainingSet, stopLearning

Methods inherited from class java.util.Observable

addObserver, clearChanged, countObservers, deleteObserver, deleteObservers, hasChanged, notifyObservers, notifyObservers, setChanged

Methods inherited from class java.lang.Object

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

Constructor Detail

DynamicBackPropagation

public DynamicBackPropagation()

DynamicBackPropagation

public DynamicBackPropagation(NeuralNetwork neuralNetwork)

Method Detail

adjustLearningRate

protected void adjustLearningRate()

adjustMomentum

protected void adjustMomentum()

doLearningEpoch

public void doLearningEpoch(TrainingSet trainingSet)

Description copied from class: SupervisedLearning

This method implements basic logic for one learning epoch for the supervised learning algorithms. Epoch is the one pass through the training set. This method iterates through the training set and trains network for each element. It also sets flag if conditions to stop learning has been reached: network error below some allowed value, or maximum iteration count

Overrides:

doLearningEpoch in class SupervisedLearning

Parameters:

trainingSet - training set for training network