org.joone.engine
Class MemoryLayer

java.lang.Object
  extended by org.joone.engine.Layer
      extended by org.joone.engine.MemoryLayer
All Implemented Interfaces:
java.io.Serializable, java.lang.Runnable, Learnable, LearnableLayer, NeuralLayer, Inspectable
Direct Known Subclasses:
DelayLayer

public abstract class MemoryLayer
extends Layer

See Also:
Serialized Form

Field Summary
protected  double[] backmemory
           
protected  double[] memory
           
 
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
MemoryLayer()
           
MemoryLayer(java.lang.String ElemName)
           
 
Method Summary
protected  void backward(double[] pattern)
          Reverse transfer function of the component.
 java.util.TreeSet check()
          Get check messages from listeners.
protected  void forward(double[] pattern)
          Transfer function to recall a result on a trained net
 int getDimension()
          Returns the number of neurons contained in the layer
 int getTaps()
          Return the taps value (06/04/00 1.08.26)
protected  void setDimensions()
          Sets the dimension of the layer.
protected  void setOutputDimension(OutputPatternListener syn)
          Sets the dimansion of the output (22/03/00 1.45.24)
 void setTaps(int newTaps)
          Inserire qui la descrizione del metodo.
protected  void sumBackInput(double[] pattern)
          Calculates the net input of the error gradents during the learning phase
 
Methods inherited from class org.joone.engine.Layer
addInputSynapse, addNoise, addOutputSynapse, adjustSizeToFwdPattern, adjustSizeToRevPattern, checkInputEnabled, checkInputs, checkOutputs, copyInto, finalize, fireFwdGet, fireFwdPut, fireRevGet, fireRevPut, fwdRun, getAllInputs, getAllOutputs, getBias, getDefaultState, getDerivative, getLastGradientInps, getLastGradientOuts, getLastInputs, getLastOutputs, getLayerName, getLearner, getMaximumState, getMinimumState, 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, setMonitor, setOutputSynapses, setRows, start, stop, sumInput, toString
 
Methods inherited from class java.lang.Object
clone, equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Field Detail

memory

protected double[] memory

backmemory

protected double[] backmemory
Constructor Detail

MemoryLayer

public MemoryLayer()

MemoryLayer

public MemoryLayer(java.lang.String ElemName)
Method Detail

getDimension

public int getDimension()
Description copied from class: Layer
Returns the number of neurons contained in the layer

Overrides:
getDimension in class Layer
Returns:
the number of neurons in the layer.

getTaps

public int getTaps()
Return the taps value (06/04/00 1.08.26)

Returns:
int

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.

Specified by:
setDimensions in class Layer

setOutputDimension

protected void setOutputDimension(OutputPatternListener syn)
Sets the dimansion of the output (22/03/00 1.45.24)

Overrides:
setOutputDimension in class Layer
Parameters:
syn - neural.engine.Synapse

setTaps

public void setTaps(int newTaps)
Inserire qui la descrizione del metodo. Data di creazione: (06/04/00 1.08.26)

Parameters:
newTaps - int

sumBackInput

protected void sumBackInput(double[] pattern)
Description copied from class: Layer
Calculates the net input of the error gradents during the learning phase

Overrides:
sumBackInput in class Layer
Parameters:
pattern - array of input values

backward

protected void backward(double[] pattern)
Reverse transfer function of the component.

Specified by:
backward in class Layer
Parameters:
pattern - double[] - input pattern on wich to apply the transfer function

forward

protected void forward(double[] pattern)
Transfer function to recall a result on a trained net

Specified by:
forward in class Layer
Parameters:
pattern - double[] - input pattern

check

public java.util.TreeSet check()
Description copied from class: Layer
Get check messages from listeners. Subclasses should call this method from thier own check method.

Specified by:
check in interface NeuralLayer
Overrides:
check in class Layer
Returns:
validation errors.
See Also:
NeuralLayer


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