org.joone.engine
Interface NeuralLayer

All Known Subinterfaces:
LearnableLayer
All Known Implementing Classes:
BiasedLinearLayer, ContextLayer, DelayLayer, GaussianLayer, GaussLayer, Layer, LinearLayer, LogarithmicLayer, MemoryLayer, NestedNeuralLayer, NetworkLayer, NeuralNet, RbfGaussianLayer, RbfLayer, SigmoidLayer, SimpleLayer, SineLayer, SoftmaxLayer, TanhLayer, WTALayer

public interface NeuralLayer

This is the interface for all the layer objects of the neural network


Method Summary
 boolean addInputSynapse(InputPatternListener newListener)
          Adds a new input synapse to the layer
 void addNoise(double amplitude)
          Adds a noise to the biases of the layer and to all the input synapses connected
 boolean addOutputSynapse(OutputPatternListener newListener)
          Adds a new output synapse to the layer
 java.util.TreeSet check()
          Validation checks for invalid parameter values, misconfiguration, etc.
 NeuralLayer copyInto(NeuralLayer newLayer)
          Copies a Layer into another one, to obtain a type-transformation from a kind of Layer to another.
 java.util.Vector getAllInputs()
          Returns the vector of the input listeners
 java.util.Vector getAllOutputs()
          Returns the vector of the input listeners
 Matrix getBias()
          Return the bias matrix
 java.lang.String getLayerName()
          Returns the name of the layer
 Monitor getMonitor()
          Returns the monitor object
 int getRows()
          Returns the dimension (# of neurons) of the Layer
 boolean isRunning()
          Returns true if the layer is running
 void removeAllInputs()
          Remove all the input listeners of the net
 void removeAllOutputs()
          Remove all the output listeners of the net
 void removeInputSynapse(InputPatternListener newListener)
          Remove an input Listener
 void removeOutputSynapse(OutputPatternListener newListener)
          Remove an output listener from the layer
 void setAllInputs(java.util.Vector newAInputPatternListener)
          Sets the vector that contains all the input listeners.
 void setAllOutputs(java.util.Vector newAOutputPatternListener)
          Sets the vector that contains all the output listeners.
 void setBias(Matrix newBias)
          Sets the matrix of biases
 void setLayerName(java.lang.String newLayerName)
          Sets the name of the layer
 void setMonitor(Monitor newMonitor)
          Sets the monitor object
 void setRows(int newRows)
          Sets the dimension (# of neurons) of the Layer
 void start()
          Starts the Layer
 

Method Detail

addNoise

void addNoise(double amplitude)
Adds a noise to the biases of the layer and to all the input synapses connected

Parameters:
amplitude - the noise's amplitude in terms of distance from zero; e.g.: a value equal 0.3 means a noise from -0.3 to 0.3

copyInto

NeuralLayer copyInto(NeuralLayer newLayer)
Copies a Layer into another one, to obtain a type-transformation from a kind of Layer to another. The old Layer is disconnected from the net, while the new Layer takes its place.

Parameters:
newLayer - neural.engine.Layer
Returns:
The new layer

getAllInputs

java.util.Vector getAllInputs()
Returns the vector of the input listeners

Returns:
java.util.Vector

getAllOutputs

java.util.Vector getAllOutputs()
Returns the vector of the input listeners

Returns:
java.util.Vector

getBias

Matrix getBias()
Return the bias matrix

Returns:
neural.engine.Matrix

getLayerName

java.lang.String getLayerName()
Returns the name of the layer

Returns:
java.lang.String

getRows

int getRows()
Returns the dimension (# of neurons) of the Layer

Returns:
int

removeAllInputs

void removeAllInputs()
Remove all the input listeners of the net


removeAllOutputs

void removeAllOutputs()
Remove all the output listeners of the net


removeInputSynapse

void removeInputSynapse(InputPatternListener newListener)
Remove an input Listener

Parameters:
newListener - the input listener to remove

removeOutputSynapse

void removeOutputSynapse(OutputPatternListener newListener)
Remove an output listener from the layer

Parameters:
newListener - the output listener to remove

setAllInputs

void setAllInputs(java.util.Vector newAInputPatternListener)
Sets the vector that contains all the input listeners. Can be useful to set the input synapses taken from another Layer

Parameters:
newAInputPatternListener - The vector containing the list of input synapses

setAllOutputs

void setAllOutputs(java.util.Vector newAOutputPatternListener)
Sets the vector that contains all the output listeners. Can be useful to set the output synapses taken from another Layer

Parameters:
newAOutputPatternListener - The vector containing the list of output synapses

setBias

void setBias(Matrix newBias)
Sets the matrix of biases

Parameters:
newBias - The Matrix object containing the biases

addInputSynapse

boolean addInputSynapse(InputPatternListener newListener)
Adds a new input synapse to the layer

Parameters:
newListener - The new input synapse
Returns:
true if the input synapse has been attached sucessfully

setLayerName

void setLayerName(java.lang.String newLayerName)
Sets the name of the layer

Parameters:
newLayerName - The name

addOutputSynapse

boolean addOutputSynapse(OutputPatternListener newListener)
Adds a new output synapse to the layer

Parameters:
newListener - The new output synapse
Returns:
true if the output synapse has been attached sucessfully

setRows

void setRows(int newRows)
Sets the dimension (# of neurons) of the Layer

Parameters:
newRows - The number of the neurons contained in the Layer

start

void start()
Starts the Layer


setMonitor

void setMonitor(Monitor newMonitor)
Sets the monitor object

Parameters:
newMonitor - The Monitor to be set

getMonitor

Monitor getMonitor()
Returns the monitor object

Returns:
java.engine.Monitor

isRunning

boolean isRunning()
Returns true if the layer is running

Returns:
boolean

check

java.util.TreeSet check()
Validation checks for invalid parameter values, misconfiguration, etc. All network components should include a check method that firstly calls its ancestor check method and adds these to any check messages it produces. This allows check messages to be collected from all levels of a component to be returned to the caller's check method. Using a TreeSet ensures that duplicate messages are removed. Check messages should be produced using the generateValidationErrorMessage method of the NetChecker class.

Returns:
validation errors.


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