C# Class SharpNeat.Phenomes.NeuralNets.FastRelaxingCyclicNetwork

A version of FastCyclicNetwork that activates a network until it becomes 'relaxed' rather than for some fixed number of iterations. This class is exactly the same as FastCyclicNetwork in all other respects; See that class for more detailed info. A network is defined as being relaxed when the change in output signal value between two successive update iterations is less than some threshold value (defined by maxAllowedSignalDelta on the constructor) for all hidden and output neurons (input and bias neurons have a fixed output value).
Inheritance: FastCyclicNetwork
Mostrar archivo Open project: colgreen/sharpneat

Public Methods

Method Description
Activate ( ) : void

Activate the network until it becomes 'relaxed' or until maxIterations is reached. If maxIterations is reached without the network relaxing then the IsValidState property will return false, although the network outputs are still provided and can be read as normal.
FastRelaxingCyclicNetwork ( FastConnection connectionArray, IActivationFunction neuronActivationFnArray, double neuronAuxArgsArray, int neuronCount, int inputNeuronCount, int outputNeuronCount, int maxTimesteps, double signalDeltaThreshold ) : System

Constructs a FastRelaxingCyclicNetwork with the provided pre-built FastConnection array and associated data.

Method Details

Activate() public method

Activate the network until it becomes 'relaxed' or until maxIterations is reached. If maxIterations is reached without the network relaxing then the IsValidState property will return false, although the network outputs are still provided and can be read as normal.
public Activate ( ) : void
return void

FastRelaxingCyclicNetwork() public method

Constructs a FastRelaxingCyclicNetwork with the provided pre-built FastConnection array and associated data.
public FastRelaxingCyclicNetwork ( FastConnection connectionArray, IActivationFunction neuronActivationFnArray, double neuronAuxArgsArray, int neuronCount, int inputNeuronCount, int outputNeuronCount, int maxTimesteps, double signalDeltaThreshold ) : System
connectionArray FastConnection
neuronActivationFnArray IActivationFunction
neuronAuxArgsArray double
neuronCount int
inputNeuronCount int
outputNeuronCount int
maxTimesteps int
signalDeltaThreshold double
return System