Uses of Class
org.aika.Iteration.Input

Packages that use Iteration.Input

Package	Description
org.aika

Uses of Iteration.Input in org.aika

Methods in org.aika that return Iteration.Input

Modifier and Type	Method and Description
Iteration.Input	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	Iteration.Input.setEndSignal(Synapse.RangeSignal endSignal)
Iteration.Input	Iteration.Input.setEndVisibility(Synapse.RangeVisibility rv) Determines if this input is used to compute the range end of the output activation.
Iteration.Input	Iteration.Input.setMatchRange(boolean matchRange) If set to true then the range of this inputs activation needs to match.
Iteration.Input	Iteration.Input.setMaxLowerWeightsSum(double maxLowerWeightsSum) MaxLowerWeightsSum is the expected sum of all weights smaller then the current weight.
Iteration.Input	Iteration.Input.setMinInput(double minInput) The minimum activation value that is required for this input.
Iteration.Input	Iteration.Input.setNeuron(Neuron neuron) Determines the input neuron.
Iteration.Input	Iteration.Input.setOptional(boolean optional) If optional is set to true, then this input is an optional part of a conjunction.
Iteration.Input	Iteration.Input.setRecurrent(boolean recurrent) If recurrent is set to true, then this input will describe an feedback loop.
Iteration.Input	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	Iteration.Input.setStartSignal(Synapse.RangeSignal startSignal)
Iteration.Input	Iteration.Input.setStartVisibility(Synapse.RangeVisibility rv) Determines if this input is used to compute the range begin of the output activation.
Iteration.Input	Iteration.Input.setWeight(Double weight) The synapse weight of this input.

Methods in org.aika with parameters of type Iteration.Input

Modifier and Type	Method and Description
int	Iteration.Input.compareTo(Iteration.Input in)
Neuron	Iteration.createAndNeuron(Neuron n, double threshold, Iteration.Input... inputs)
Neuron	Iteration.createNeuron(Neuron n, double bias, Iteration.Input... inputs)
Neuron	Iteration.createOrNeuron(Neuron n, Iteration.Input... inputs)

Method parameters in org.aika with type arguments of type Iteration.Input

Modifier and Type	Method and Description
Neuron	Iteration.createAndNeuron(Neuron n, double threshold, Collection<Iteration.Input> inputs) Creates a neuron representing a conjunction of its inputs.
Neuron	Iteration.createNeuron(Neuron n, double bias, Collection<Iteration.Input> inputs)
Neuron	Iteration.createOrNeuron(Neuron n, Set<Iteration.Input> inputs) Creates a neuron representing a disjunction of its inputs.