Uses of Class
simbad.piconode.core.node.Node

Packages that use Node
simbad.piconode.core.arc   
simbad.piconode.core.node   
 

Uses of Node in simbad.piconode.core.arc
 

Fields in simbad.piconode.core.arc declared as Node
protected  Node Arc._source
           
protected  Node Arc._target
           
 

Methods in simbad.piconode.core.arc that return Node
 Node ModularArc.getSource()
           
 Node Arc.getSource()
           
 Node ModularArc.getTarget()
           
 Node Arc.getTarget()
           
 

Constructors in simbad.piconode.core.arc with parameters of type Node
Arc(Node __source, Node __target)
           
ModularArc(Node __source, int __inIndex, Node __target)
           
ModularArc(Node __source, Node __target)
           
 

Uses of Node in simbad.piconode.core.node
 

Subclasses of Node in simbad.piconode.core.node
 class ConnectedNode
          The abstract ConnectedNode class contains the basis for defining a node that is part of a Network module.
 class FeedForwardNeuralNetwork
          This class implement a simple feed-forward neural network (no special properties)
 class FeedForwardNeuralNetworkForBackPropLearning
          This class implement a feed-forward neural network with learning capabilitie through back-propagation.
 class ModularNode
           
 class Module
          The abstract Module class provides the minimal setting to define modular node, i.e.
 class Network
          The Network class provides the minimal basis to define a network module.
 class NeuralNetwork
          The NeuralNetwork class provides the minimal basis to define a neural network module.
 class Neuron
          The neuron class contains every thing needed to embed a functional neuron into a NeuralNetwork module.
 class NeuronalNode
           
 class NeuronForBackPropLearning
          The NeuronForBackPropLearning class extends a Neuron with methods that makes it possible to embed such neurons into NeuralNetworks with Back-propagation learning ability (e.g.
 class RecurrentNeuralNetwork
          This class implements the basis for a recurrent neural network (no special ability).
 class RecurrentNeuron
           
 class SelfOrganizingMap
          This class implement a simple 2D "Kohonen" Self Organizing Map.
 class SOMoutputNeuron
          !n : [major optimisation issue] this class may be suppressed and re-implemented as arrays in the SelfOrganizingMap class
 class ValueContainer
          a ValueContainer object contains a simple double value and may be linked from and to other objects.