C# 클래스 Encog.Neural.Networks.Synapse.NEAT.NEATSynapse

Implements a NEAT network as a synapse between two layers. In Encog, a NEAT network is created by using a NEATSynapse between an input and output layer. NEAT networks only have an input and an output layer. There are no actual hidden layers. Rather this synapse will evolve many hidden neurons that have connections that are not easily defined by layers. Connections can be feedforward, recurrent, or self-connected. NEAT networks relieve the programmer of the need to define the hidden layer structure of the neural network. The output from the neural network can be calculated normally or using a snapshot. The snapshot mode is slower, but it can be more accurate. The snapshot handles recurrent layers better, as it takes the time to loop through the network multiple times to "flush out" the recurrent links. NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the generation of evolving artificial neural networks. It was developed by Ken Stanley while at The University of Texas at Austin. http://www.cs.ucf.edu/~kstanley/
상속: Encog.Persist.BasicPersistedSubObject, ISynapse, IContextClearable
파일 보기 프로젝트 열기: encog/encog-silverlight-core 1 사용 예제들

공개 메소드들

메소드 설명
ClearContext ( ) : void

Clear any context.

Clone ( ) : object

A clone of this object.

Compute ( INeuralData input ) : INeuralData

Compute the output from this synapse.

CreatePersistor ( ) : IPersistor

A persistor to load/save this type of synapse.

NEATSynapse ( ) : System

Default constructor.

NEATSynapse ( ILayer fromLayer, ILayer toLayer ) : System

Create a NEAT synapse.

NEATSynapse ( ILayer fromLayer, ILayer toLayer, IList neurons, IActivationFunction activationFunction, int networkDepth ) : System

Construct a NEAT synapse.

getNeurons ( ) : IList

The NEAT neurons.

메소드 상세

ClearContext() 공개 메소드

Clear any context.
public ClearContext ( ) : void
리턴 void

Clone() 공개 메소드

A clone of this object.
public Clone ( ) : object
리턴 object

Compute() 공개 메소드

Compute the output from this synapse.
public Compute ( INeuralData input ) : INeuralData
input INeuralData The input to this synapse.
리턴 INeuralData

CreatePersistor() 공개 메소드

A persistor to load/save this type of synapse.
public CreatePersistor ( ) : IPersistor
리턴 IPersistor

NEATSynapse() 공개 메소드

Default constructor.
public NEATSynapse ( ) : System
리턴 System

NEATSynapse() 공개 메소드

Create a NEAT synapse.
public NEATSynapse ( ILayer fromLayer, ILayer toLayer ) : System
fromLayer ILayer The from layer.
toLayer ILayer The to layer.
리턴 System

NEATSynapse() 공개 메소드

Construct a NEAT synapse.
public NEATSynapse ( ILayer fromLayer, ILayer toLayer, IList neurons, IActivationFunction activationFunction, int networkDepth ) : System
fromLayer ILayer The input layer.
toLayer ILayer The output layer.
neurons IList The neurons in this synapse.
activationFunction IActivationFunction The activation function to use.
networkDepth int The depth of the network.
리턴 System

getNeurons() 공개 메소드

The NEAT neurons.
public getNeurons ( ) : IList
리턴 IList