//Constructors
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="numOfNeurons">The number of neurons.</param>
/// <param name="activationCfg">The configuration of the activation function.</param>
public HiddenLayerSettings(int numOfNeurons, IActivationSettings activationCfg)
{
NumOfNeurons = numOfNeurons;
ActivationCfg = (IActivationSettings)activationCfg.DeepClone();
Check();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="outputActivationCfg">Configuration of the output layer activation function.</param>
/// <param name="hiddenLayersCfg">The configuration of the hidden layers. Hidden layers are optional.</param>
/// <param name="trainerCfg">The configuration of the associated trainer.</param>
public FeedForwardNetworkSettings(IActivationSettings outputActivationCfg,
HiddenLayersSettings hiddenLayersCfg,
RCNetBaseSettings trainerCfg
)
{
OutputActivationCfg = (IActivationSettings)outputActivationCfg.DeepClone();
HiddenLayersCfg = hiddenLayersCfg == null ? new HiddenLayersSettings() : (HiddenLayersSettings)hiddenLayersCfg.DeepClone();
TrainerCfg = trainerCfg.DeepClone();
Check();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="name">The name of the neuron group.</param>
/// <param name="relShare">Specifies how big relative portion of pool's neurons is formed by this group of the neurons.</param>
/// <param name="activationCfg">The common configuration of the neurons' activation function.</param>
/// <param name="predictorsCfg">The common configuration of the predictors provider.</param>
/// <param name="homogenousExcitabilityCfg">The configuration of the neurons homogenous excitability.</param>
/// <param name="biasCfg">The configuration of the constant input bias.</param>
public SpikingNeuronGroupSettings(string name,
double relShare,
IActivationSettings activationCfg,
PredictorsProviderSettings predictorsCfg,
HomogenousExcitabilitySettings homogenousExcitabilityCfg = null,
RandomValueSettings biasCfg = null
)
{
Name = name;
RelShare = relShare;
ActivationCfg = (IActivationSettings)activationCfg.DeepClone();
PredictorsCfg = (PredictorsProviderSettings)predictorsCfg.DeepClone();
HomogenousExcitabilityCfg = homogenousExcitabilityCfg == null ? new HomogenousExcitabilitySettings() : (HomogenousExcitabilitySettings)homogenousExcitabilityCfg.DeepClone();
BiasCfg = biasCfg == null ? null : (RandomValueSettings)biasCfg.DeepClone();
Check();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="name">The name of the neuron group.</param>
/// <param name="relShare">Specifies how big relative portion of pool's neurons is formed by this group of the neurons.</param>
/// <param name="activationCfg">The common configuration of the neurons' activation function.</param>
/// <param name="predictorsCfg">The common configuration of the predictors provider.</param>
/// <param name="firingThreshold">The firing threshold value. Every time the current normalized activation is higher than the normalized past reference activation by at least this threshold, it is evaluated as a firing event.</param>
/// <param name="thresholdMaxRefDeepness">Maximum age of the past activation for the evaluation of the firing event.</param>
/// <param name="biasCfg">The configuration of the constant input bias.</param>
/// <param name="retainmentCfg">The configuration of the neurons' retainment property.</param>
public AnalogNeuronGroupSettings(string name,
double relShare,
IActivationSettings activationCfg,
PredictorsProviderSettings predictorsCfg,
double firingThreshold = DefaultFiringThreshold,
int thresholdMaxRefDeepness = DefaultThresholdMaxRefDeepness,
RandomValueSettings biasCfg = null,
RetainmentSettings retainmentCfg = null
)
{
Name = name;
RelShare = relShare;
ActivationCfg = (IActivationSettings)activationCfg.DeepClone();
PredictorsCfg = (PredictorsProviderSettings)predictorsCfg.DeepClone();
FiringThreshold = firingThreshold;
ThresholdMaxRefDeepness = thresholdMaxRefDeepness;
BiasCfg = biasCfg == null ? null : (RandomValueSettings)biasCfg.DeepClone();
RetainmentCfg = retainmentCfg == null ? null : (RetainmentSettings)retainmentCfg.DeepClone();
Check();
return;
}