org.joone.structure

Class Nakayama

java.lang.Object

org.joone.structure.Nakayama

All Implemented Interfaces:

java.io.Serializable, java.util.EventListener, ConvergenceListener, NeuralNetListener, NeuralValidationListener

public class Nakayama
extends java.lang.Object
implements NeuralNetListener, NeuralValidationListener, ConvergenceListener, java.io.Serializable

This class performs the method of optimizing activation functions as described in:

K.Nakayama and Y.Kimura, "Optimization of activation functions in multilayer neural network applied to pattern classification", Proc. IEEE ICNN'94 Florida, pp.431-436, June 1994.

This techniques probably fails whenever the NeuralNet.join() method is called because this optimization technique stops the network to perform the optimization, use a NeuralNetListener instead.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Nakayama(NeuralNet aNet) Creates a new instance of Nakayama.

Method Summary

Modifier and Type	Method and Description
void	addLayer(Layer aLayer) Adds layers to this optimizer.
void	addLayers(NeuralNet aNeuralNet) Adds all the hidden layers to this optimizer.
void	cicleTerminated(NeuralNetEvent e)
void	errorChanged(NeuralNetEvent e)
double	getEpsilon() Gets epsilon, the threshold to decide if a neuron should be deleted or not.
void	netConverged(ConvergenceEvent anEvent, ConvergenceObserver anObserver) This method is called whenever the network has converged according to some ConvergenceObserver
void	netStarted(NeuralNetEvent e)
void	netStopped(NeuralNetEvent e)
void	netStoppedError(NeuralNetEvent e, java.lang.String error)
void	netValidated(NeuralValidationEvent event)
boolean	optimize() Optimizes the activation functions of the neural network.
void	setEpsilon(double anEpsilon) Sets epsilon, the threshold to decide if a neuron should be deleted or not.

Methods inherited from class java.lang.Object

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

Constructor Detail

Nakayama

public Nakayama(NeuralNet aNet)

Creates a new instance of Nakayama.

Parameters:

aNet - the network to be optimized.

Method Detail

addLayer

public void addLayer(Layer aLayer)

Adds layers to this optimizer. The layers will be optimized. Layers should be on the same (layer) level, otherwise the optimization does not make sense.

Parameters:

aLayer - the layer to be added.

addLayers

public void addLayers(NeuralNet aNeuralNet)

Adds all the hidden layers to this optimizer. The layers will be optimized. The neuron network should consist of only one hidden layer, i.e. the hidden layers should be on the same level else this method doesn't make any sense. If the hidden layers are not all on the same level then the layers should be added individually my using , adding only the layers that are on the same hidden level.

Parameters:

aNeuralNet - the network holding the hidden layers.

optimize

public boolean optimize()

Optimizes the activation functions of the neural network.

Returns:

whether the network was optimized or not, i.e. if neurons where deleted or not.

cicleTerminated

public void cicleTerminated(NeuralNetEvent e)

Specified by:

cicleTerminated in interface NeuralNetListener

errorChanged

public void errorChanged(NeuralNetEvent e)

Specified by:

errorChanged in interface NeuralNetListener

netStarted

public void netStarted(NeuralNetEvent e)

Specified by:

netStarted in interface NeuralNetListener

netStopped

public void netStopped(NeuralNetEvent e)

Specified by:

netStopped in interface NeuralNetListener

netStoppedError

public void netStoppedError(NeuralNetEvent e,
                            java.lang.String error)

Specified by:

netStoppedError in interface NeuralNetListener

netValidated

public void netValidated(NeuralValidationEvent event)

Specified by:

netValidated in interface NeuralValidationListener

getEpsilon

public double getEpsilon()

Gets epsilon, the threshold to decide if a neuron should be deleted or not.

Returns:

the threshold epsilon.

setEpsilon

public void setEpsilon(double anEpsilon)

Sets epsilon, the threshold to decide if a neuron should be deleted or not.

Parameters:

anEpsilon - the new epsilon.

netConverged

public void netConverged(ConvergenceEvent anEvent,
                         ConvergenceObserver anObserver)

Description copied from interface: ConvergenceListener

This method is called whenever the network has converged according to some ConvergenceObserver

Specified by:

netConverged in interface ConvergenceListener

Parameters:

anEvent - the event that is generated.

anObserver - the observer that generated the event.