org.aika

Class Iteration.Input

java.lang.Object

org.aika.Iteration.Input

All Implemented Interfaces:

Comparable<Iteration.Input>

Enclosing class:

Iteration

public static class Iteration.Input
extends Object
implements Comparable<Iteration.Input>

Field Summary

Fields

Modifier and Type	Field and Description
Integer	absoluteRid
Synapse.RangeSignal	endSignal
Synapse.RangeVisibility	endVisibility
boolean	matchRange
double	maxLowerWeightsSum
double	minInput
Neuron	neuron
boolean	optional
boolean	recurrent
Integer	relativeRid
Synapse.RangeSignal	startSignal
Synapse.RangeVisibility	startVisibility
double	weight

Constructor Summary

Constructors

Constructor and Description
Input()

Method Summary

Modifier and Type	Method and Description
int	compareTo(Iteration.Input in)
Iteration.Input	setAbsoluteRid(Integer absoluteRid) If the absolute relational id (rid) not null, then it is required to match the rid of input activation.
Iteration.Input	setEndSignal(Synapse.RangeSignal endSignal)
Iteration.Input	setEndVisibility(Synapse.RangeVisibility rv) Determines if this input is used to compute the range end of the output activation.
Iteration.Input	setMatchRange(boolean matchRange) If set to true then the range of this inputs activation needs to match.
Iteration.Input	setMaxLowerWeightsSum(double maxLowerWeightsSum) MaxLowerWeightsSum is the expected sum of all weights smaller then the current weight.
Iteration.Input	setMinInput(double minInput) The minimum activation value that is required for this input.
Iteration.Input	setNeuron(Neuron neuron) Determines the input neuron.
Iteration.Input	setOptional(boolean optional) If optional is set to true, then this input is an optional part of a conjunction.
Iteration.Input	setRecurrent(boolean recurrent) If recurrent is set to true, then this input will describe an feedback loop.
Iteration.Input	setRelativeRid(Integer relativeRid) The relative relational id (rid) determines the relative position of this inputs rid with respect to other inputs of this neuron.
Iteration.Input	setStartSignal(Synapse.RangeSignal startSignal)
Iteration.Input	setStartVisibility(Synapse.RangeVisibility rv) Determines if this input is used to compute the range begin of the output activation.
Iteration.Input	setWeight(Double weight) The synapse weight of this input.

Methods inherited from class java.lang.Object

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

Field Detail

recurrent

public boolean recurrent

optional

public boolean optional

neuron

public Neuron neuron

weight

public double weight

maxLowerWeightsSum

public double maxLowerWeightsSum

minInput

public double minInput

matchRange

public boolean matchRange

startVisibility

public Synapse.RangeVisibility startVisibility

endVisibility

public Synapse.RangeVisibility endVisibility

startSignal

public Synapse.RangeSignal startSignal

endSignal

public Synapse.RangeSignal endSignal

relativeRid

public Integer relativeRid

absoluteRid

public Integer absoluteRid

Constructor Detail

Input

public Input()

Method Detail

setRecurrent

public Iteration.Input setRecurrent(boolean recurrent)

If recurrent is set to true, then this input will describe an feedback loop. The input neuron may depend on the output of this neuron.

Parameters:

recurrent -

Returns:

setOptional

public Iteration.Input setOptional(boolean optional)

If optional is set to true, then this input is an optional part of a conjunction. This is only used for the method createAndNeuron.

Parameters:

optional -

Returns:

setNeuron

public Iteration.Input setNeuron(Neuron neuron)

Determines the input neuron.

Parameters:

neuron -

Returns:

setMaxLowerWeightsSum

public Iteration.Input setMaxLowerWeightsSum(double maxLowerWeightsSum)

MaxLowerWeightsSum is the expected sum of all weights smaller then the current weight. It is used as an hint to compute the boolean representation of this neuron.

Parameters:

maxLowerWeightsSum -

Returns:

setWeight

public Iteration.Input setWeight(Double weight)

The synapse weight of this input.

Parameters:

weight -

Returns:

setMinInput

public Iteration.Input setMinInput(double minInput)

The minimum activation value that is required for this input. The minInput value is used to compute the neurons bias.

Parameters:

minInput -

Returns:

setAbsoluteRid

public Iteration.Input setAbsoluteRid(Integer absoluteRid)

If the absolute relational id (rid) not null, then it is required to match the rid of input activation.

Parameters:

absoluteRid -

Returns:

setRelativeRid

public Iteration.Input setRelativeRid(Integer relativeRid)

The relative relational id (rid) determines the relative position of this inputs rid with respect to other inputs of this neuron.

Parameters:

relativeRid -

Returns:

setMatchRange

public Iteration.Input setMatchRange(boolean matchRange)

If set to true then the range of this inputs activation needs to match.

Parameters:

matchRange -

Returns:

setStartVisibility

public Iteration.Input setStartVisibility(Synapse.RangeVisibility rv)

Determines if this input is used to compute the range begin of the output activation.

Parameters:

rv -

Returns:

setEndVisibility

public Iteration.Input setEndVisibility(Synapse.RangeVisibility rv)

Determines if this input is used to compute the range end of the output activation.

Parameters:

rv -

Returns:

setStartSignal

public Iteration.Input setStartSignal(Synapse.RangeSignal startSignal)

setEndSignal

public Iteration.Input setEndSignal(Synapse.RangeSignal endSignal)

compareTo

public int compareTo(Iteration.Input in)

Specified by:

compareTo in interface Comparable<Iteration.Input>