//Constructor
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="location">The neuron's location.</param>
/// <param name="analogActivation">The instance of an analog activation function.</param>
/// <param name="bias">The constant bias.</param>
/// <param name="firingThreshold">The firing threshold value. It must be GE0 and LT1. 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="firingThresholdMaxRefDeepness">Maximum age of the past activation for the evaluation of the firing event.</param>
/// <param name="retainmentStrength">The strength of the analog neuron's retainment property. It enables the leaky integrator feature of the neuron.</param>
/// <param name="predictorsProviderCfg">The configuration of the predictors provider.</param>
public HiddenNeuron(NeuronLocation location,
AFAnalogBase analogActivation,
double bias,
double firingThreshold,
int firingThresholdMaxRefDeepness,
double retainmentStrength,
PredictorsProviderSettings predictorsProviderCfg
)
{
Location = location;
Statistics = new NeuronStatistics();
Bias = bias;
//Activation check
if (analogActivation.TypeOfActivation == ActivationType.Spiking)
{
throw new ArgumentException($"Wrong type of the activation function.", "analogActivation");
}
_activationFn = analogActivation;
_analogFiringThreshold = firingThreshold;
_histActivationsQueue = firingThresholdMaxRefDeepness < 2 ? null : new SimpleQueue <double>(firingThresholdMaxRefDeepness);
_analogRetainmentStrength = retainmentStrength;
_predictorsProvider = predictorsProviderCfg != null ? new PredictorsProvider(predictorsProviderCfg) : null;
OutputData = new NeuronOutputData();
Reset(false);
return;
}
/// <summary>
/// Creates configuration of the group of analog neurons having a TanH activation.
/// </summary>
/// <param name="groupName">The name of the group</param>
/// <param name="relShare">The relative share. It determines how big part of the pool neurons will be occupied by this neuron group.</param>
private AnalogNeuronGroupSettings CreateTanHGroup(string groupName, double relShare)
{
//Each neuron within the group will have its own constant bias
//selected from the range -0.05 to 0.05 using gaussian (normal) distribution
RandomValueSettings biasCfg = new RandomValueSettings(-0.05, 0.05, false, new GaussianDistrSettings(0, 1));
//We want retainment property to be set for every neuron within the group
const double RetainmentDensity = 1d;
//Each neuron will have its own constant retainment strength
//selected from the range 0 to 0.75 using uniform distribution
URandomValueSettings retainmentStrengthCfg = new URandomValueSettings(0, 0.75);
RetainmentSettings retainmentCfg = new RetainmentSettings(RetainmentDensity, retainmentStrengthCfg);
//Predictors configuration
//We will use the Activation and ActivationPower predictors
PredictorsProviderSettings predictorsCfg = new PredictorsProviderSettings(new PredictorActivationSettings(),
new PredictorActivationPowerSettings()
);
//Create the neuron group configuration
AnalogNeuronGroupSettings groupCfg = new AnalogNeuronGroupSettings(groupName,
relShare,
new AFAnalogTanHSettings(),
predictorsCfg,
AnalogNeuronGroupSettings.DefaultFiringThreshold,
AnalogNeuronGroupSettings.DefaultThresholdMaxRefDeepness,
biasCfg,
retainmentCfg
);
return(groupCfg);
}
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="elem">A xml element containing the configuration data.</param>
public AnalogNeuronGroupSettings(XElement elem)
{
//Validation
XElement settingsElem = Validate(elem, XsdTypeName);
//Parsing
//Name
Name = settingsElem.Attribute("name").Value;
//Relative share
RelShare = double.Parse(settingsElem.Attribute("relShare").Value, CultureInfo.InvariantCulture);
//Activation settings
ActivationCfg = ActivationFactory.LoadSettings(settingsElem.Elements().First());
//Firing threshold
FiringThreshold = double.Parse(settingsElem.Attribute("firingThreshold").Value, CultureInfo.InvariantCulture);
ThresholdMaxRefDeepness = int.Parse(settingsElem.Attribute("thresholdMaxRefDeepness").Value, CultureInfo.InvariantCulture);
//Bias
XElement biasSettingsElem = settingsElem.Elements("bias").FirstOrDefault();
BiasCfg = biasSettingsElem == null ? null : new RandomValueSettings(biasSettingsElem);
//Retainment
XElement retainmentSettingsElem = settingsElem.Elements("retainment").FirstOrDefault();
RetainmentCfg = retainmentSettingsElem == null ? null : new RetainmentSettings(retainmentSettingsElem);
//Predictors
PredictorsCfg = new PredictorsProviderSettings(settingsElem.Elements("predictors").First());
Check();
return;
}
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="elem">A xml element containing the configuration data.</param>
public SpikingNeuronGroupSettings(XElement elem)
{
//Validation
XElement settingsElem = Validate(elem, XsdTypeName);
//Parsing
//Name
Name = settingsElem.Attribute("name").Value;
//Relative share
RelShare = double.Parse(settingsElem.Attribute("relShare").Value, CultureInfo.InvariantCulture);
//Activation settings
ActivationCfg = ActivationFactory.LoadSettings(settingsElem.Elements().First());
//Homogenous excitability
XElement homogenousExcitabilityElem = settingsElem.Elements("homogenousExcitability").FirstOrDefault();
HomogenousExcitabilityCfg = homogenousExcitabilityElem == null ? new HomogenousExcitabilitySettings() : new HomogenousExcitabilitySettings(homogenousExcitabilityElem);
//Bias
XElement biasSettingsElem = settingsElem.Elements("bias").FirstOrDefault();
BiasCfg = biasSettingsElem == null ? null : new RandomValueSettings(biasSettingsElem);
//Predictors
PredictorsCfg = new PredictorsProviderSettings(settingsElem.Elements("predictors").First());
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;
}
/// <summary>
/// Creates the configuration of neuron group having the specified spiking activation function.
/// </summary>
/// <param name="activationCfg">The activation function configuration.</param>
/// <param name="predictorsCfg">The predictors provider configuration.</param>
/// <param name="excitabilityCfg">The configuration of the homogenous excitability.</param>
/// <param name="steadyBias">The constant bias (0 means no bias).</param>
private SpikingNeuronGroupSettings CreateSpikingGroup(IActivationSettings activationCfg,
PredictorsProviderSettings predictorsCfg,
HomogenousExcitabilitySettings excitabilityCfg,
double steadyBias = 0d
)
{
//Bias configuration
RandomValueSettings biasCfg = steadyBias == 0 ? null : new RandomValueSettings(steadyBias, steadyBias);
//Create neuron group configuration
SpikingNeuronGroupSettings groupCfg = new SpikingNeuronGroupSettings(BuildNeuronGroupName(activationCfg),
1d,
activationCfg,
predictorsCfg,
excitabilityCfg,
biasCfg
);
return(groupCfg);
}
//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;
}
//Constructor
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="location">The neuron's location.</param>
/// <param name="spikingActivation">The instance of a spiking activation function.</param>
/// <param name="bias">The constant bias.</param>
/// <param name="predictorsProviderCfg">The configuration of the predictors provider.</param>
public HiddenNeuron(NeuronLocation location,
AFSpikingBase spikingActivation,
double bias,
PredictorsProviderSettings predictorsProviderCfg
)
{
Location = location;
Statistics = new NeuronStatistics();
Bias = bias;
//Activation check
if (spikingActivation.TypeOfActivation == ActivationType.Analog)
{
//Spiking
throw new ArgumentException($"Wrong type of the activation function.", "spikingActivation");
}
_activationFn = spikingActivation;
_analogFiringThreshold = 0;
_histActivationsQueue = null;
_analogRetainmentStrength = 0;
_predictorsProvider = predictorsProviderCfg != null ? new PredictorsProvider(predictorsProviderCfg) : null;
OutputData = new NeuronOutputData();
Reset(false);
return;
}
/// <summary>
/// Creates the configuration of neuron group having the specified analog activation function.
/// </summary>
/// <param name="activationCfg">The activation function configuration.</param>
/// <param name="predictorsCfg">The predictors provider configuration.</param>
/// <param name="maxAbsBias">The maximum absolute value of the bias (0 means no bias).</param>
/// <param name="maxRetainmentStrength">The maximum retainment strength (0 means no retainment).</param>
private AnalogNeuronGroupSettings CreateAnalogGroup(IActivationSettings activationCfg,
PredictorsProviderSettings predictorsCfg,
double maxAbsBias = 0d,
double maxRetainmentStrength = 0d
)
{
//Bias configuration
RandomValueSettings biasCfg = maxAbsBias == 0 ? null : new RandomValueSettings(-maxAbsBias, maxAbsBias);
//Retainment configuration
const double RetainmentDensity = 1d;
RetainmentSettings retainmentCfg = maxRetainmentStrength == 0 ? null : new RetainmentSettings(RetainmentDensity, new URandomValueSettings(0, maxRetainmentStrength));
//Create neuron group configuration
AnalogNeuronGroupSettings groupCfg = new AnalogNeuronGroupSettings(BuildNeuronGroupName(activationCfg),
1d,
activationCfg,
predictorsCfg,
AnalogNeuronGroupSettings.DefaultFiringThreshold,
AnalogNeuronGroupSettings.DefaultThresholdMaxRefDeepness,
biasCfg,
retainmentCfg
);
return(groupCfg);
}
/// <summary>
/// Creates the simplified configuration of the state machine following the pure LSM design.
/// </summary>
/// <param name="totalSize">The total number of hidden neurons.</param>
/// <param name="spikingActivationCfg">The configuration of the spiking activation function.</param>
/// <param name="excitabilityCfg">The homogenous excitability configuration.</param>
/// <param name="inputConnectionDensity">The density of the input field connections to hidden neurons.</param>
/// <param name="maxInputDelay">The maximum delay of an input synapse.</param>
/// <param name="interconnectionDensity">The density of the hidden neurons recurrent interconnection.</param>
/// <param name="maxInternalDelay">The maximum delay of an internal synapse.</param>
/// <param name="steadyBias">The constant bias (0 means no bias).</param>
/// <param name="predictorsProviderCfg">The configuration of the predictors provider.</param>
public StateMachineSettings CreatePureLSMCfg(int totalSize,
IActivationSettings spikingActivationCfg,
HomogenousExcitabilitySettings excitabilityCfg,
double inputConnectionDensity,
int maxInputDelay,
double interconnectionDensity,
int maxInternalDelay,
double steadyBias,
PredictorsProviderSettings predictorsProviderCfg
)
{
//Check NP is not bypassed
if (BypassedNP)
{
throw new InvalidOperationException("Neural preprocessor is bypassed thus LSM design can't be created.");
}
//Activation check
if (ActivationFactory.CreateAF(spikingActivationCfg, new Random()).TypeOfActivation != ActivationType.Spiking)
{
throw new ArgumentException("Specified activation must be spiking.", "spikingActivationCfg");
}
//One neuron group
SpikingNeuronGroupSettings grp = CreateSpikingGroup(spikingActivationCfg, predictorsProviderCfg, excitabilityCfg, steadyBias);
//Simple spiking pool
PoolSettings poolCfg = new PoolSettings(BuildPoolName(ActivationContent.Spiking, 0),
new ProportionsSettings(totalSize, 1, 1),
new NeuronGroupsSettings(grp),
new InterconnSettings(new RandomSchemaSettings(interconnectionDensity, 0d, false, false))
);
//Simple reservoir structure
ReservoirStructureSettings resStructCfg = new ReservoirStructureSettings(BuildResStructName(ActivationContent.Spiking, 0),
new PoolsSettings(poolCfg)
);
//Input connections configuration
List <InputConnSettings> inputConns = new List <InputConnSettings>(InputEncoderCfg.VaryingFieldsCfg.ExternalFieldsCfg.FieldCfgCollection.Count);
foreach (ExternalFieldSettings fieldCfg in InputEncoderCfg.VaryingFieldsCfg.ExternalFieldsCfg.FieldCfgCollection)
{
InputConnSettings inputConnCfg = new InputConnSettings(fieldCfg.Name,
poolCfg.Name,
inputConnectionDensity,
0
);
inputConns.Add(inputConnCfg);
}
//Synapse general configuration
SpikingSourceSTInputSettings spikingSourceSTInputSettings = new SpikingSourceSTInputSettings(new URandomValueSettings(0, 1), new PlasticitySTInputSettings(new NonlinearDynamicsSTInputSettings()));
SpikingSourceSTExcitatorySettings spikingSourceSTExcitatorySettings = new SpikingSourceSTExcitatorySettings(new URandomValueSettings(0, 1), new PlasticitySTExcitatorySettings(new NonlinearDynamicsSTExcitatorySettings()));
SpikingSourceSTInhibitorySettings spikingSourceSTInhibitorySettings = new SpikingSourceSTInhibitorySettings(new URandomValueSettings(0, 1), new PlasticitySTInhibitorySettings(new NonlinearDynamicsSTInhibitorySettings()));
SynapseSTInputSettings synapseSTInputSettings = new SynapseSTInputSettings(Synapse.SynapticDelayMethod.Random, maxInputDelay, null, spikingSourceSTInputSettings);
SynapseSTExcitatorySettings synapseSTExcitatorySettings = new SynapseSTExcitatorySettings(Synapse.SynapticDelayMethod.Random, maxInternalDelay, 4, null, spikingSourceSTExcitatorySettings);
SynapseSTInhibitorySettings synapseSTInhibitorySettings = new SynapseSTInhibitorySettings(Synapse.SynapticDelayMethod.Random, maxInternalDelay, 1, null, spikingSourceSTInhibitorySettings);
SynapseSTSettings synapseSTCfg = new SynapseSTSettings(synapseSTInputSettings, synapseSTExcitatorySettings, synapseSTInhibitorySettings);
SynapseSettings synapseCfg = new SynapseSettings(synapseSTCfg, null);
//Create reservoir instance
ReservoirInstanceSettings resInstCfg = new ReservoirInstanceSettings(GetResInstName(ResDesign.PureLSM, 0),
resStructCfg.Name,
new InputConnsSettings(inputConns),
synapseCfg
);
//Build and return SM configuration
return(new StateMachineSettings(new NeuralPreprocessorSettings(InputEncoderCfg,
new ReservoirStructuresSettings(resStructCfg),
new ReservoirInstancesSettings(resInstCfg)
),
ReadoutLayerCfg
));
}
/// <summary>
/// Creates the simplified configuration of the state machine following the pure ESN design.
/// </summary>
/// <param name="totalSize">The total number of hidden neurons.</param>
/// <param name="maxInputStrength">The max sum of weights of input synapses per an analog hidden neuron (see the constant DefaultAnalogMaxInputStrength).</param>
/// <param name="inputConnectionDensity">The density of the input field connections to hidden neurons.</param>
/// <param name="maxInputDelay">The maximum delay of an input synapse.</param>
/// <param name="interconnectionDensity">The density of the hidden neurons recurrent interconnection.</param>
/// <param name="maxInternalDelay">The maximum delay of an internal synapse.</param>
/// <param name="maxAbsBias">The maximum absolute value of the bias (0 means no bias).</param>
/// <param name="maxRetainmentStrength">The maximum retainment strength (0 means no retainment).</param>
/// <param name="predictorsProviderCfg">The configuration of the predictors provider.</param>
public StateMachineSettings CreatePureESNCfg(int totalSize,
double maxInputStrength,
double inputConnectionDensity,
int maxInputDelay,
double interconnectionDensity,
int maxInternalDelay,
double maxAbsBias,
double maxRetainmentStrength,
PredictorsProviderSettings predictorsProviderCfg
)
{
//Check NP is not bypassed
if (BypassedNP)
{
throw new InvalidOperationException("Neural preprocessor is bypassed thus ESN design can't be created.");
}
//Default ESN activation
IActivationSettings analogActivationCfg = new AFAnalogTanHSettings();
//One neuron group
AnalogNeuronGroupSettings grp = CreateAnalogGroup(analogActivationCfg, predictorsProviderCfg, maxAbsBias, maxRetainmentStrength);
//Simple analog pool
PoolSettings poolCfg = new PoolSettings(BuildPoolName(ActivationContent.Analog, 0),
new ProportionsSettings(totalSize, 1, 1),
new NeuronGroupsSettings(grp),
new InterconnSettings(new RandomSchemaSettings(interconnectionDensity))
);
//Simple reservoir structure
ReservoirStructureSettings resStructCfg = new ReservoirStructureSettings(BuildResStructName(ActivationContent.Analog, 0),
new PoolsSettings(poolCfg)
);
//Input connections configuration
List <InputConnSettings> inputConns = new List <InputConnSettings>(InputEncoderCfg.VaryingFieldsCfg.ExternalFieldsCfg.FieldCfgCollection.Count);
foreach (ExternalFieldSettings fieldCfg in InputEncoderCfg.VaryingFieldsCfg.ExternalFieldsCfg.FieldCfgCollection)
{
InputConnSettings inputConnCfg = new InputConnSettings(fieldCfg.Name,
poolCfg.Name,
0,
inputConnectionDensity
);
inputConns.Add(inputConnCfg);
}
//Synapse general configuration
SynapseATInputSettings synapseATInputSettings = new SynapseATInputSettings(Synapse.SynapticDelayMethod.Random, maxInputDelay, new AnalogSourceSettings(new URandomValueSettings(0d, maxInputStrength)));
SynapseATIndifferentSettings synapseATIndifferentSettings = new SynapseATIndifferentSettings(Synapse.SynapticDelayMethod.Random, maxInternalDelay);
SynapseATSettings synapseATCfg = new SynapseATSettings(SynapseATSettings.DefaultSpectralRadiusNum, synapseATInputSettings, synapseATIndifferentSettings);
SynapseSettings synapseCfg = new SynapseSettings(null, synapseATCfg);
//Create reservoir instance
ReservoirInstanceSettings resInstCfg = new ReservoirInstanceSettings(GetResInstName(ResDesign.PureESN, 0),
resStructCfg.Name,
new InputConnsSettings(inputConns),
synapseCfg
);
//Build and return SM configuration
return(new StateMachineSettings(new NeuralPreprocessorSettings(InputEncoderCfg,
new ReservoirStructuresSettings(resStructCfg),
new ReservoirInstancesSettings(resInstCfg)
),
ReadoutLayerCfg
));
}
