org.encog.neural.freeform

Interface FreeformNeuron

All Superinterfaces:

TempTrainingData

All Known Implementing Classes:

BasicFreeformNeuron, FreeformContextNeuron

public interface FreeformNeuron
extends TempTrainingData

This interface defines a freeform neuron. By freeform that this neuron is not necessarily part of a layer.

Method Summary

Modifier and Type	Method and Description
void	addInput(FreeformConnection inputConnection) Add an input connection to this neuron.
void	addOutput(FreeformConnection outputConnection) Add an output connection to this neuron.
double	getActivation()
InputSummation	getInputSummation()
java.util.List<FreeformConnection>	getOutputs()
double	getSum()
boolean	isBias()
void	performCalculation() Perform the internal calculation for this neuron.
void	setActivation(double activation) Set the activation, or final output for this neuron.
void	setBias(boolean b) Determine if this neuron is a bias neuron.
void	setInputSummation(InputSummation theInputSummation) Set the input summation method.
void	updateContext() Update the context value for this neuron.

Methods inherited from interface org.encog.neural.freeform.TempTrainingData

addTempTraining, allocateTempTraining, clearTempTraining, getTempTraining, setTempTraining

Method Detail

addInput

void addInput(FreeformConnection inputConnection)

Add an input connection to this neuron.

Parameters:

inputConnection - The input connection.

addOutput

void addOutput(FreeformConnection outputConnection)

Add an output connection to this neuron.

Parameters:

outputConnection - The output connection.

getActivation

double getActivation()

Returns:

The activation for this neuron. This is the final output after the activation function has been applied.

getInputSummation

InputSummation getInputSummation()

Returns:

The input summation method.

getOutputs

java.util.List<FreeformConnection> getOutputs()

Returns:

The outputs from this neuron.

getSum

double getSum()

Returns:

The output sum for this neuron. This is the output prior to the activation function being applied.

isBias

boolean isBias()

Returns:

True, if this is a bias neuron.

performCalculation

void performCalculation()

Perform the internal calculation for this neuron.

setActivation

void setActivation(double activation)

Set the activation, or final output for this neuron.

Parameters:

activation - THe activation.

setBias

void setBias(boolean b)

Determine if this neuron is a bias neuron.

Parameters:

b - True, if this neuron is considered a bias neuron.

setInputSummation

void setInputSummation(InputSummation theInputSummation)

Set the input summation method.

Parameters:

theInputSummation - The input summation method.

updateContext

void updateContext()

Update the context value for this neuron.