Uses of Class
org.aika.neuron.Activation

Packages that use Activation

Package	Description
org.aika
org.aika.corpus
org.aika.lattice
org.aika.neuron
org.aika.training

Uses of Activation in org.aika

Methods in org.aika 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	Neuron.addInput(Document doc, int begin, int end) Propagate an input activation into the network.
Activation	Neuron.addInput(Document doc, int begin, int end, Integer relationalId) Propagate an input activation into the network.

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

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

Uses of Activation in org.aika.corpus

Fields in org.aika.corpus declared as Activation

Modifier and Type	Field and Description
Activation	InterpretationNode.activation

Fields in org.aika.corpus with type parameters of type Activation

Modifier and Type	Field and Description
TreeMap<NodeActivation.Key,Activation>	Document.activationsByRid
TreeSet<Activation>	Document.inputNeuronActivations
NavigableSet<Activation>	InterpretationNode.neuronActivations
ArrayDeque<Activation>	Document.UpperBoundQueue.queue
ArrayList<TreeSet<Activation>>	Document.ValueQueue.queue

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

Modifier and Type	Method and Description
Stream<Activation>	Document.getFinalActivations()
Collection<Activation>	InterpretationNode.getNeuronActivations()

Methods in org.aika.corpus 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)
void	Document.ValueQueue.propagateWeight(int round, Activation act)

Uses of Activation in org.aika.lattice

Methods in org.aika.lattice that return Activation

Modifier and Type	Method and Description
protected Activation	OrNode.createActivation(Document doc, NodeActivation.Key ak)

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

Modifier and Type	Method and Description
void	OrNode.apply(Document doc, Activation act)
void	OrNode.propagateAddedActivation(Document doc, Activation act)
void	OrNode.register(Activation act, Document doc)

Uses of Activation in org.aika.neuron

Fields in org.aika.neuron declared as Activation

Modifier and Type	Field and Description
Activation	Activation.SynapseActivation.input
Activation	Activation.SynapseActivation.output

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

Modifier and Type	Field and Description
TreeMap<NodeActivation.Key,Activation>	INeuron.ThreadState.activations
TreeMap<NodeActivation.Key,Activation>	INeuron.ThreadState.activationsEnd
TreeMap<NodeActivation.Key,Activation>	INeuron.ThreadState.activationsRid

Methods in org.aika.neuron that return Activation

Modifier and Type	Method and Description
Activation	INeuron.addInput(Document doc, Activation.Builder input) Propagate an input activation into the network.
static Activation	Activation.get(Document doc, INeuron n, Integer rid, Range r, Range.Relation rr, InterpretationNode o, InterpretationNode.Relation or)
static Activation	Activation.get(Document doc, INeuron n, NodeActivation.Key ak)
Activation	Activation.StateChange.getActivation()
Activation	INeuron.getFirstActivation(Document doc)

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

Modifier and Type	Method and Description
Collection<Activation>	INeuron.getActivations(Document doc)
static Stream<Activation>	Activation.getActivationsByRange(INeuron.ThreadState th, INeuron n, Integer rid, Range r, Range.Relation rr, InterpretationNode o, InterpretationNode.Relation or)
Collection<Activation>	INeuron.getAllActivations(Document doc)
Collection<Activation>	INeuron.getFinalActivations(Document doc) getFinalActivations is a convenience method to retrieve all activations of the given neuron that are part of the final interpretation.
static Stream<Activation>	Activation.select(Document doc, INeuron n, Integer rid, Range r, Range.Relation rr, InterpretationNode o, InterpretationNode.Relation or)
static Stream<Activation>	Activation.select(INeuron.ThreadState th, INeuron n, Integer rid, Range r, Range.Relation rr, InterpretationNode o, InterpretationNode.Relation or)

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

Modifier and Type	Method and Description
void	INeuron.computeBounds(Activation act)
Activation.State	INeuron.computeWeight(int round, Activation act)
void	INeuron.linkNeuronRelations(Document doc, Activation act) Sets the incoming and outgoing links between neuron activations.
void	INeuron.propagateAddedActivation(Document doc, Activation act)

Constructors in org.aika.neuron with parameters of type Activation

Constructor and Description
SynapseActivation(Synapse s, Activation input, Activation output)

Uses of Activation in org.aika.training

Fields in org.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 org.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)