org.joone.engine
Class BiasedLinearLayer

java.lang.Object
  extended by org.joone.engine.Layer
      extended by org.joone.engine.SimpleLayer
          extended by org.joone.engine.BiasedLinearLayer
All Implemented Interfaces:
java.io.Serializable, java.lang.Runnable, Learnable, LearnableLayer, NeuralLayer, Inspectable

public class BiasedLinearLayer
extends SimpleLayer
implements LearnableLayer

This layer consists of linear neurons, i.e. neurons that sum up their inputs (actually this is done by the (full) synapse in Joone) along with their biases. In the learning process the biases are adjusted in an attempt to output a value closer to the desired output. This layer differs from LinearLayer in two ways: - This layer uses biases. These biases can/will also be adjusted in the learning process. - It has no scalar beta parameter.

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
BiasedLinearLayer()
          Creates a new instance of BiasedLinearLayer
BiasedLinearLayer(java.lang.String anElemName)
          Creates a new instance of BiasedLinearLayer.
 
Method Summary
 void backward(double[] pattern)
          Reverse transfer function of the component.
 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
 Learner getLearner()
          Deprecated. - Used only for backward compatibility
 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, 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
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

BiasedLinearLayer

public BiasedLinearLayer()
Creates a new instance of BiasedLinearLayer


BiasedLinearLayer

public BiasedLinearLayer(java.lang.String anElemName)
Creates a new instance of BiasedLinearLayer.

Parameters:
The - name of the layer.
Method Detail

backward

public void backward(double[] pattern)
Description copied from class: Layer
Reverse transfer function of the component.

Overrides:
backward in class SimpleLayer
Parameters:
pattern - input pattern on which to apply the transfer function

getDerivative

public double getDerivative(int i)
Similar to the backward message and used by RTRL

Specified by:
getDerivative in class Layer

forward

public void forward(double[] pattern)
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

getLearner

public Learner getLearner()
Deprecated. - Used only for backward compatibility

Description copied from class: Layer
Returns the appropriate Learner object for this class depending on the Monitor.learningMode property value

Specified by:
getLearner in interface Learnable
Overrides:
getLearner in class Layer
Returns:
the Learner object if applicable, otherwise null
See Also:
Learnable.getLearner()

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


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