Uses of Class
network.aika.neuron.activation.Activation

Packages that use Activation

Package	Description
network.aika
network.aika.lattice
network.aika.neuron
network.aika.neuron.activation
network.aika.neuron.relation
network.aika.training

Uses of Activation in network.aika

Fields in network.aika with type parameters of type Activation

Modifier and Type	Field and Description
static Comparator<Activation>	Document.ACTIVATIONS_OUTPUT_COMPARATOR
TreeMap<Document.ActKey,Activation>	Document.activationsByRangeBegin
TreeMap<Document.ActKey,Activation>	Document.activationsByRangeEnd
ArrayList<Activation>	Document.addedActivations
TreeSet<Activation>	Document.inputNeuronActivations
ArrayDeque<Activation>	Document.UpperBoundQueue.queue
ArrayList<TreeSet<Activation>>	Document.ValueQueue.queue

Methods in network.aika that return types with arguments of type Activation

Modifier and Type	Method and Description
Stream<Activation>	Document.getActivations()
Stream<Activation>	Document.getFinalActivations()

Methods in network.aika with parameters of type Activation

Modifier and Type	Method and Description
void	Document.UpperBoundQueue.add(Activation act)
void	Document.ValueQueue.add(int round, Activation act)
double	DistanceFunction.f(Activation iAct, Activation oAct)
void	Document.ValueQueue.propagateActivationValue(int round, Activation act)

Uses of Activation in network.aika.lattice

Methods in network.aika.lattice that return Activation

Modifier and Type	Method and Description
Activation	OrNode.OrActivation.getInputActivation(int i)
abstract Activation	NodeActivation.getInputActivation(int i)
Activation	InputNode.InputActivation.getInputActivation(int i)
Activation	AndNode.AndActivation.getInputActivation(int i)

Methods in network.aika.lattice with parameters of type Activation

Modifier and Type	Method and Description
void	InputNode.addActivation(Activation inputAct)
void	OrNode.apply(Activation act)
void	OrNode.discover(Activation act, PatternDiscovery.Config config)
void	OrNode.propagate(Activation act)

Constructors in network.aika.lattice with parameters of type Activation

Constructor and Description
InputActivation(int id, Activation iAct, InputNode node)
Link(Activation iAct, InputNode.InputActivation oAct)

Uses of Activation in network.aika.neuron

Fields in network.aika.neuron with type parameters of type Activation

Modifier and Type	Field and Description
TreeMap<INeuron.ActKey,Activation>	INeuron.ThreadState.activations
TreeMap<INeuron.ActKey,Activation>	INeuron.ThreadState.activationsEnd

Methods in network.aika.neuron that return Activation

Modifier and Type	Method and Description
Activation	Neuron.addInput(Document doc, Activation.Builder inputAct) Propagate an input activation into the network.
Activation	INeuron.addInput(Document doc, Activation.Builder input) Propagate an input activation into the network.
Activation	Neuron.addInput(Document doc, int begin, int end) Propagate an input activation into the network.
Activation	Neuron.addInput(Document doc, Range r) Propagate an input activation into the network.
Activation	Neuron.getActivation(Document doc, Range r, boolean onlyFinal)
Activation	INeuron.getActivation(Document doc, Range r, boolean onlyFinal)

Methods in network.aika.neuron that return types with arguments of type Activation

Modifier and Type	Method and Description
Collection<Activation>	Neuron.getActivations(Document doc, boolean onlyFinal) getFinalActivations is a convenience method to retrieve all activations of the given neuron that are part of the final interpretation.
Collection<Activation>	INeuron.getActivations(Document doc, boolean onlyFinal)

Methods in network.aika.neuron with parameters of type Activation

Modifier and Type	Method and Description
void	INeuron.propagate(Activation act)
void	INeuron.register(Activation act)

Uses of Activation in network.aika.neuron.activation

Fields in network.aika.neuron.activation declared as Activation

Modifier and Type	Field and Description
Activation	Candidate.activation
Activation	Activation.Link.input
Activation	Activation.Link.output

Fields in network.aika.neuron.activation with type parameters of type Activation

Modifier and Type	Field and Description
static Comparator<Activation>	Activation.ACTIVATION_ID_COMP
Map<Activation,Activation.StateChange>	SearchNode.modifiedActs

Methods in network.aika.neuron.activation that return Activation

Modifier and Type	Method and Description
Activation	Activation.StateChange.getActivation()

Methods in network.aika.neuron.activation that return types with arguments of type Activation

Modifier and Type	Method and Description
Collection<Activation>	Activation.getConflicts()

Methods in network.aika.neuron.activation with parameters of type Activation

Modifier and Type	Method and Description
static void	SearchNode.invalidateCachedDecision(Activation act)
void	Linker.link(Activation act, OrNode.Link ol) Adds the incoming links between neuron activations.

Method parameters in network.aika.neuron.activation with type arguments of type Activation

Modifier and Type	Method and Description
void	Activation.saveOldState(Map<Activation,Activation.StateChange> changes, long v)

Constructors in network.aika.neuron.activation with parameters of type Activation

Constructor and Description
Candidate(Activation act, int id)
Link(Synapse s, Activation input, Activation output)

Uses of Activation in network.aika.neuron.relation

Methods in network.aika.neuron.relation that return types with arguments of type Activation

Modifier and Type	Method and Description
abstract Collection<Activation>	Relation.getActivations(INeuron n, Activation linkedAct)
Collection<Activation>	RangeRelation.getActivations(INeuron n, Activation linkedAct)
Collection<Activation>	InstanceRelation.getActivations(INeuron n, Activation linkedAct)
static Collection<Activation>	RangeRelation.getActivationsByRangeEquals(INeuron.ThreadState th, Range r, Range.Relation rr)

Methods in network.aika.neuron.relation with parameters of type Activation

Modifier and Type	Method and Description
abstract Collection<Activation>	Relation.getActivations(INeuron n, Activation linkedAct)
Collection<Activation>	RangeRelation.getActivations(INeuron n, Activation linkedAct)
Collection<Activation>	InstanceRelation.getActivations(INeuron n, Activation linkedAct)
abstract boolean	Relation.test(Activation act, Activation linkedAct)
boolean	RangeRelation.test(Activation act, Activation linkedAct)
boolean	InstanceRelation.test(Activation act, Activation linkedAct)

Uses of Activation in network.aika.training

Fields in network.aika.training with type parameters of type Activation

Modifier and Type	Field and Description
TreeSet<Activation>	SupervisedTraining.errorSignalActivations
TreeSet<Activation>	SupervisedTraining.BackPropagationQueue.queue
TreeSet<Activation>	SupervisedTraining.targetActivations

Methods in network.aika.training with parameters of type Activation

Modifier and Type	Method and Description
void	SupervisedTraining.BackPropagationQueue.add(Activation act)
void	SupervisedTraining.computeBackpropagationErrorSignal(Activation act)
void	SupervisedTraining.computeOutputErrorSignal(Activation act)
SynapseEvaluation.Result	SynapseEvaluation.evaluate(Synapse s, Activation iAct, Activation oAct) Determines whether a synapse should be created between two neurons during training.
static void	LongTermLearning.longTermDepression(Document doc, LongTermLearning.Config config, Activation act, boolean dir) The long-term depression algorithm decreases the strength of a synapse if only one side of the synapse is firing.
static void	LongTermLearning.longTermPotentiation(Document doc, LongTermLearning.Config config, Activation act) The long-term potentiation algorithm is a variant of the Hebb learning rule.
void	SupervisedTraining.train(INeuron n, Activation targetAct, double learnRate, SynapseEvaluation se)
void	SupervisedTraining.updateErrorSignal(Activation act)