org.neuroph.nnet.learning
Class BackPropagation
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
- All Implemented Interfaces:
- java.io.Serializable, java.lang.Runnable
public class BackPropagation
- extends SigmoidDeltaRule
The BackPropagation class is the Back Propagation learning rule for
Multi Layer Perceptron neural networks.
- See Also:
- Serialized Form
Field Summary |
private static long |
serialVersionUID
The class fingerprint that is set to indicate serialization
compatibility with a previous version of the class. |
Constructor Summary |
BackPropagation(NeuralNetwork neuralNetwork)
Creates new instance of BackPropagation learning for the specified neural network |
Method Summary |
private void |
adjustHiddenLayers()
This method implements weights adjustment for the hidden layers |
private double |
calculateDelta(Neuron neuron)
Calculates and returns delta parameter (neuron error) for the specified
neuron |
protected void |
updateNetworkWeights(java.util.Vector<java.lang.Double> patternError)
This method implements weight update procedure for the whole network
for the specified error vector |
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 |
serialVersionUID
private static final long serialVersionUID
- The class fingerprint that is set to indicate serialization
compatibility with a previous version of the class.
- See Also:
- Constant Field Values
BackPropagation
public BackPropagation(NeuralNetwork neuralNetwork)
- Creates new instance of BackPropagation learning for the specified neural network
- Parameters:
neuralNetwork
-
updateNetworkWeights
protected void updateNetworkWeights(java.util.Vector<java.lang.Double> patternError)
- This method implements weight update procedure for the whole network
for the specified error vector
- Overrides:
updateNetworkWeights
in class SigmoidDeltaRule
- Parameters:
patternError
- single pattern error vector
adjustHiddenLayers
private void adjustHiddenLayers()
- This method implements weights adjustment for the hidden layers
calculateDelta
private double calculateDelta(Neuron neuron)
- Calculates and returns delta parameter (neuron error) for the specified
neuron
- Parameters:
neuron
- neuron to calculate error for
- Returns:
- delta (neuron error) for the specified neuron