org.joone.engine

Class RbfGaussianLayer

java.lang.Object

org.joone.engine.Layer

org.joone.engine.RbfLayer

org.joone.engine.RbfGaussianLayer

All Implemented Interfaces:

java.io.Serializable, java.lang.Runnable, Learnable, LearnableLayer, NeuralLayer, Inspectable

public class RbfGaussianLayer
extends RbfLayer

This class implements the nonlinear layer in Radial Basis Function (RBF) networks using Gaussian functions.

Author:

Boris Jansen

See Also:

Serialized Form

Field Summary

Fields inherited from class org.joone.engine.Layer

bias, gradientInps, gradientOuts, inps, inputPatternListeners, learnable, learning, m_batch, monitor, myLearner, outputPatternListeners, outs, running, step, STOP_FLAG

Constructor Summary

Constructors

Constructor and Description
RbfGaussianLayer() Creates a new instance of RbfGaussianLayer

Method Summary

Methods

Modifier and Type	Method and Description
protected void	backward(double[] pattern) Reverse transfer function of the component.
protected void	forward(double[] pattern) Transfer function to recall a result on a trained net
double	getDefaultState() Return the default state of a node in this layer, such as 0 for a tanh or 0.5 for a sigmoid layer
double	getDerivative(int i) Similar to the backward message and used by RTRL
RbfGaussianParameters[]	getGaussianParameters() Gets the parameters that define the Gaussian RBFs.
double	getMaximumState() Return maximum value of a node in this layer
double	getMinimumState() Return minimum value of a node in this layer
java.util.Collection	Inspections() It doesn't make sense to return biases for this layer
protected void	setDimensions() Sets the dimension of the layer.
void	setGaussianParameters(RbfGaussianParameters[] aGaussianParameters) Sets the parameters that define the Gaussian RBFs.
void	useRandomCenter(StreamInputSynapse aStreamInput) Sets the Gaussian parameters to centers chosen randomly from the input/training data.

Methods inherited from class org.joone.engine.RbfLayer

adjustSizeToFwdPattern

Methods inherited from class org.joone.engine.Layer

addInputSynapse, addNoise, addOutputSynapse, adjustSizeToRevPattern, check, checkInputEnabled, checkInputs, checkOutputs, copyInto, finalize, fireFwdGet, fireFwdPut, fireRevGet, fireRevPut, fwdRun, getAllInputs, getAllOutputs, getBias, getDimension, getLastGradientInps, getLastGradientOuts, getLastInputs, getLastOutputs, getLayerName, getLearner, getMonitor, getRows, getThreadMonitor, hasStepCounter, init, initLearner, InspectableTitle, isInputLayer, isOutputLayer, isRunning, join, randomize, randomizeBias, randomizeWeights, removeAllInputs, removeAllOutputs, removeInputSynapse, removeListener, removeOutputSynapse, resetInputListeners, revRun, run, setAllInputs, setAllOutputs, setBias, setConnDimensions, setInputDimension, setInputSynapses, setLastInputs, setLastOutputs, setLayerName, setMonitor, setOutputDimension, setOutputSynapses, setRows, start, stop, sumBackInput, sumInput, toString

Methods inherited from class java.lang.Object

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

Constructor Detail

RbfGaussianLayer

public RbfGaussianLayer()

Creates a new instance of RbfGaussianLayer

Method Detail

backward

protected void backward(double[] pattern)
                 throws JooneRuntimeException

Description copied from class: Layer

Reverse transfer function of the component.

Specified by:

backward in class Layer

Parameters:

pattern - input pattern on which to apply the transfer function

Throws:

JooneRuntimeException

getDerivative

public double getDerivative(int i)

Similar to the backward message and used by RTRL

Specified by:

getDerivative in class Layer

forward

protected void forward(double[] pattern)
                throws JooneRuntimeException

Description copied from class: Layer

Transfer function to recall a result on a trained net

Specified by:

forward in class Layer

Parameters:

pattern - input pattern to which to apply the rtransfer function

Throws:

JooneRuntimeException

setDimensions

protected void setDimensions()

Description copied from class: Layer

Sets the dimension of the layer. Override to define how the internal buffers must be sized.

Overrides:

setDimensions in class RbfLayer

getGaussianParameters

public RbfGaussianParameters[] getGaussianParameters()

Gets the parameters that define the Gaussian RBFs.

Returns:

the Gaussian RBFs parameters.

setGaussianParameters

public void setGaussianParameters(RbfGaussianParameters[] aGaussianParameters)

Sets the parameters that define the Gaussian RBFs.

Parameters:

aGaussianParameters - The new parameters for the RBFs.

useRandomCenter

public void useRandomCenter(StreamInputSynapse aStreamInput)

Sets the Gaussian parameters to centers chosen randomly from the input/training data.

Parameters:

aStreamInput - the synapse providing the input, from where we will select random centers.

Inspections

public java.util.Collection Inspections()

It doesn't make sense to return biases for this layer

Specified by:

Inspections in interface Inspectable

Overrides:

Inspections in class Layer

Returns:

null

See Also:

org.joone.Inspection

getDefaultState

public double getDefaultState()

Description copied from class: Layer

Return the default state of a node in this layer, such as 0 for a tanh or 0.5 for a sigmoid layer

Specified by:

getDefaultState in class Layer

getMinimumState

public double getMinimumState()

Description copied from class: Layer

Return minimum value of a node in this layer

Specified by:

getMinimumState in class Layer

getMaximumState

public double getMaximumState()

Description copied from class: Layer

Return maximum value of a node in this layer

Specified by:

getMaximumState in class Layer