org.joone.engine

Class SineLayer

java.lang.Object

org.joone.engine.Layer

org.joone.engine.SimpleLayer

org.joone.engine.SineLayer

All Implemented Interfaces:

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

public class SineLayer
extends SimpleLayer
implements LearnableLayer

The output of a sine layer neuron is the sum of the weighted input values, applied to a sine (sin(x)). Neurons with sine activation problems might be useful in problems with periodicity.

Author:

Boris Jansen

See Also:

parent, parent, implemented interface, 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
SineLayer() Creates a new instance of SineLayer
SineLayer(java.lang.String aName) Creates a new instance of SineLayer

Method Summary

Methods

Modifier and Type	Method and Description
void	backward(double[] aPattern) Reverse transfer function of the component.
protected void	forward(double[] aPattern) 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
double	getMaximumState() Return maximum value of a node in this layer
double	getMinimumState() Return minimum value of a node in this layer

Methods inherited from class org.joone.engine.SimpleLayer

getLearningRate, getLrate, getMomentum, setDimensions, setLrate, setMomentum, setMonitor

Methods inherited from class org.joone.engine.Layer

addInputSynapse, addNoise, addOutputSynapse, adjustSizeToFwdPattern, 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, Inspections, isInputLayer, isOutputLayer, isRunning, join, randomize, randomizeBias, randomizeWeights, removeAllInputs, removeAllOutputs, removeInputSynapse, removeListener, removeOutputSynapse, resetInputListeners, revRun, run, setAllInputs, setAllOutputs, setBias, setConnDimensions, setInputDimension, setInputSynapses, setLastInputs, setLastOutputs, setLayerName, setOutputDimension, setOutputSynapses, setRows, start, stop, sumBackInput, sumInput, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.joone.engine.Learnable

getLearner, getMonitor, initLearner

Methods inherited from interface org.joone.engine.NeuralLayer

addInputSynapse, addNoise, addOutputSynapse, check, copyInto, getAllInputs, getAllOutputs, getBias, getLayerName, getMonitor, getRows, isRunning, removeAllInputs, removeAllOutputs, removeInputSynapse, removeOutputSynapse, setAllInputs, setAllOutputs, setBias, setLayerName, setMonitor, setRows, start

Constructor Detail

SineLayer

public SineLayer()

Creates a new instance of SineLayer

SineLayer

public SineLayer(java.lang.String aName)

Creates a new instance of SineLayer

Parameters:

aName - The name of the layer

Method Detail

forward

protected void forward(double[] aPattern)
                throws JooneRuntimeException

Description copied from class: Layer

Transfer function to recall a result on a trained net

Specified by:

forward in class Layer

Parameters:

aPattern - input pattern to which to apply the rtransfer function

Throws:

JooneRuntimeException

backward

public void backward(double[] aPattern)
              throws JooneRuntimeException

Description copied from class: Layer

Reverse transfer function of the component.

Overrides:

backward in class SimpleLayer

Parameters:

aPattern - 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

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