ITK: itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector

template<class TMeasurementVector, class TTargetVector>

typedef SmartPointer<const Self> itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::ConstPointer

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 46 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::InputFunctionInterfaceType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::InputFunctionInterfaceType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 60 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

typedef int itk::LightObject::InternalReferenceCountType [protected, inherited]

Define the type of the reference count according to the target. This allows the use of atomic operations

Definition at line 139 of file itkLightObject.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::LayerInterfaceType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::LayerInterfaceType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 53 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::LayerVectorType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::LayerVectorType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 57 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

typedef LearningFunctionBase<typename TLearningLayer::LayerInterfaceType, TTargetVector> itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::LearningFunctionInterfaceType [inherited]

Definition at line 48 of file itkMultilayerNeuralNetworkBase.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::LearningLayerType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::LearningLayerType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 54 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::MeasurementVectorType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::MeasurementVectorType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 49 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::NetworkOutputType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::NetworkOutputType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 51 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef SmartPointer<Self> itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::Pointer

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 45 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef OneHiddenLayerBackPropagationNeuralNetwork itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::Self

Standard class typedefs.

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 43 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef MultilayerNeuralNetworkBase<TMeasurementVector, TTargetVector, BackPropagationLayer<TMeasurementVector, TTargetVector> > itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::Superclass

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 44 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::TargetVectorType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::TargetVectorType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 50 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::TransferFunctionInterfaceType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::TransferFunctionInterfaceType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 59 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::ValueType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::ValueType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 48 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

typedef Superclass::WeightVectorType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::WeightVectorType

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Definition at line 56 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector>

itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::OneHiddenLayerBackPropagationNeuralNetwork ( ) [protected]

template<class TMeasurementVector, class TTargetVector>

virtual itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::~OneHiddenLayerBackPropagationNeuralNetwork ( ) [inline, protected, virtual]

Definition at line 107 of file itkOneHiddenLayerBackPropagationNeuralNetwork.h.

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

void itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::AddLayer ( LayerInterfaceType * ) [inherited]

unsigned long itk::Object::AddObserver	(	const EventObject &	event,
		Command *
	)			const `[inherited]`

unsigned long itk::Object::AddObserver	(	const EventObject &	event,
		Command *
	)			`[inherited]`

Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

void itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::AddWeightSet ( typename LayerInterfaceType::WeightSetInterfaceType * ) [inherited]

template<class TMeasurementVector, class TTargetVector>

virtual void itk::Statistics::NeuralNetworkObject< TMeasurementVector, TTargetVector >::BackwardPropagate ( NetworkOutputType errors ) [pure virtual, inherited]

Implemented in itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, itk::Statistics::BackPropagationLayer< TMeasurementVector, TTargetVector > >.

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

virtual void itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::BackwardPropagate ( NetworkOutputType errors ) [virtual, inherited]

static void itk::LightObject::BreakOnError ( ) [static, inherited]

This method is called when itkExceptionMacro executes. It allows the debugger to break on error.

virtual void itk::DataObject::CopyInformation ( const DataObject * ) [inline, virtual, inherited]

Copy information from the specified data set. This method is part of the pipeline execution model. By default, a ProcessObject will copy meta-data from the first input to all of its outputs. See ProcessObject::GenerateOutputInformation(). Each subclass of DataObject is responsible for being able to copy whatever meta-data it needs from from another DataObject. The default implementation of this method is empty. If a subclass overrides this method, it should always call its superclass' version.

Definition at line 439 of file itkDataObject.h.

virtual LightObject::Pointer itk::Object::CreateAnother ( ) const [virtual, inherited]

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::LightObject.

void itk::DataObject::DataHasBeenGenerated ( ) [inherited]

Inform the pipeline mechanism that data has been generated. This method is called by ProcessObject::UpdateOutputData() once the process object has finished generating its data. This essentially marks the DataObject as being updated and ready for use.

virtual void itk::Object::DebugOff ( ) const [virtual, inherited]

Turn debugging output off.

virtual void itk::Object::DebugOn ( ) const [virtual, inherited]

Turn debugging output on.

virtual void itk::LightObject::Delete ( ) [virtual, inherited]

Delete an itk object. This method should always be used to delete an object when the new operator was used to create it. Using the C delete method will not work with reference counting.

void itk::DataObject::DisconnectPipeline ( ) [inherited]

Separate this data object from the pipeline. This routine disconnects a data object from the upstream pipeline. Hence an Update() from downstream will not propagate back past this data object. To completely isolate this data object from the pipeline, the application must remove this data object from any filters which it is connected as the input.

template<class TMeasurementVector, class TTargetVector>

virtual NetworkOutputType itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::GenerateOutput ( TMeasurementVector samplevector ) [virtual]

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

Command* itk::Object::GetCommand ( unsigned long tag ) [inherited]

Get the command associated with the given tag. NOTE: This returns a pointer to a Command, but it is safe to asign this to a Command::Pointer. Since Command inherits from LightObject, at this point in the code, only a pointer or a reference to the Command can be used.

bool itk::DataObject::GetDataReleased ( ) const [inline, inherited]

Get the flag indicating the data has been released.

Definition at line 334 of file itkDataObject.h.

bool itk::Object::GetDebug ( ) const [inherited]

Get the value of the debug flag.

template<class TMeasurementVector, class TTargetVector>

virtual const ValueType& itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::GetFirstHiddenLayerBias ( ) [virtual]

static bool itk::DataObject::GetGlobalReleaseDataFlag ( ) [static, inherited]

static bool itk::Object::GetGlobalWarningDisplay ( ) [static, inherited]

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

const LayerInterfaceType* itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::GetLayer ( int layer_id ) const [inherited]

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

LayerInterfaceType* itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::GetLayer ( int layer_id ) [inherited]

const MetaDataDictionary& itk::Object::GetMetaDataDictionary ( void ) const [inherited]

Returns:: A constant reference to this objects MetaDataDictionary.

MetaDataDictionary& itk::Object::GetMetaDataDictionary ( void ) [inherited]

Returns:: A reference to this objects MetaDataDictionary.

Warning:: This reference may be changed.

virtual unsigned long itk::Object::GetMTime ( ) const [virtual, inherited]

Return this objects modified time.

Referenced by itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >::GetObjectMTime().

template<class TMeasurementVector, class TTargetVector>

virtual const char* itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::GetNameOfClass ( ) const [virtual]

Run-time type information (and related methods).

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

template<class TMeasurementVector, class TTargetVector>

virtual const unsigned int& itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::GetNumOfFirstHiddenNodes ( ) [virtual]

template<class TMeasurementVector, class TTargetVector>

virtual const unsigned int& itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::GetNumOfInputNodes ( ) [virtual]

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

int itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::GetNumOfLayers ( void ) const [inline, inherited]

Definition at line 64 of file itkMultilayerNeuralNetworkBase.h.

template<class TMeasurementVector, class TTargetVector>

virtual const unsigned int& itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::GetNumOfOutputNodes ( ) [virtual]

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

int itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::GetNumOfWeightSets ( void ) const [inline, inherited]

Definition at line 68 of file itkMultilayerNeuralNetworkBase.h.

template<class TMeasurementVector, class TTargetVector>

virtual const ValueType& itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::GetOutputLayerBias ( ) [virtual]

virtual const unsigned long& itk::DataObject::GetPipelineMTime ( ) [virtual, inherited]

virtual int itk::LightObject::GetReferenceCount ( ) const [inline, virtual, inherited]

Gets the reference count on this object.

Definition at line 106 of file itkLightObject.h.

virtual const bool& itk::DataObject::GetReleaseDataFlag ( ) [virtual, inherited]

SmartPointerForwardReference<ProcessObject> itk::DataObject::GetSource ( ) const [inherited]

Get the process object that generated this data object. If there is no process object, then the data object has been disconnected from the pipeline, or the data object was created manually. (Note: we cannot use the GetObjectMacro() defined in itkMacro because the mutual dependency of DataObject and ProcessObject causes compile problems. Also, a forward reference smart pointer is returned, not a smart pointer, because of the circular dependency between the process and data object.)

GetSource() returns a SmartPointerForwardReference and not a WeakPointer because it is assumed the code calling GetSource() wants to hold a long term reference to the source.

unsigned int itk::DataObject::GetSourceOutputIndex ( ) const [inherited]

Which of the source's outputs corresponds to this data object?

virtual unsigned long itk::DataObject::GetUpdateMTime ( ) const [virtual, inherited]

MTime for the last time this DataObject was generated.

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

LayerInterfaceType::WeightSetInterfaceType* itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::GetWeightSet ( unsigned int id ) [inline, inherited]

Definition at line 80 of file itkMultilayerNeuralNetworkBase.h.

void itk::DataObject::GlobalReleaseDataFlagOff ( ) [inline, inherited]

Definition at line 319 of file itkDataObject.h.

void itk::DataObject::GlobalReleaseDataFlagOn ( ) [inline, inherited]

Definition at line 317 of file itkDataObject.h.

static void itk::Object::GlobalWarningDisplayOff ( ) [inline, static, inherited]

Definition at line 100 of file itkObject.h.

References itk::Object::SetGlobalWarningDisplay().

static void itk::Object::GlobalWarningDisplayOn ( ) [inline, static, inherited]

Definition at line 98 of file itkObject.h.

References itk::Object::SetGlobalWarningDisplay().

virtual void itk::DataObject::Graft ( const DataObject * ) [inline, virtual, inherited]

Method for grafting the content of one data object into another one. This method is intended to be overloaded by derived classes. Each one of them should use dynamic_casting in order to verify that the grafted object is actually of the same type as the class on which the Graft() method was invoked.

Definition at line 453 of file itkDataObject.h.

bool itk::Object::HasObserver ( const EventObject & event ) const [inherited]

Return true if an observer is registered for this event.

template<class TMeasurementVector, class TTargetVector>

void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::Initialize ( ) [virtual]

Restore the data object to its initial state. This means releasing memory.

Reimplemented from itk::DataObject.

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

void itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::InitializeWeights ( ) [inherited]

Reimplemented in itk::Statistics::RBFNetwork< TMeasurementVector, TTargetVector >.

void itk::Object::InvokeEvent ( const EventObject & ) const [inherited]

Call Execute on all the Commands observing this event id. The actions triggered by this call doesn't modify this object.

void itk::Object::InvokeEvent ( const EventObject & ) [inherited]

Call Execute on all the Commands observing this event id.

virtual void itk::Object::Modified ( ) const [virtual, inherited]

Update the modification time for this object. Many filters rely on the modification time to determine if they need to recompute their data.

Referenced by itk::NarrowBandImageFilterBase< TInputImage, itk::Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::InsertNarrowBandNode(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::HistogramAlgorithmBase< TInputHistogram >::SetInputHistogram(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::NarrowBandImageFilterBase< TInputImage, itk::Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBand(), itk::NarrowBandImageFilterBase< TInputImage, itk::Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandInnerRadius(), itk::NarrowBandImageFilterBase< TInputImage, itk::Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandTotalRadius(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints1(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints2(), itk::NonUniformBSpline< TDimension >::SetSplineOrder(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< TInputHistogram >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

template<class TMeasurementVector, class TTargetVector>

static Pointer itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::New ( ) [static]

New macro for creation of through a Smart Pointer.

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

virtual void itk::DataObject::PrepareForNewData ( ) [inline, virtual, inherited]

Setup a DataObject to receive new data. This method is called by the pipeline mechanism on each output of filter that needs to execute. The default implementation is to return a DataObject to its initial state. This may involve releasing previously allocated bulk data. Subclasses of DataObject may want to override this method and/or the Initialize() method if they want a different default behavior (for instance a DataObject might want finer control over its bulk data memory management).

Definition at line 389 of file itkDataObject.h.

void itk::LightObject::Print	(	std::ostream &	os,
		Indent	indent = `0`
	)			const `[inherited]`

Cause the object to print itself out.

Referenced by itk::WeakPointer< itk::ProcessObject >::Print().

virtual void itk::LightObject::PrintHeader	(	std::ostream &	os,
		Indent	indent
	)			const `[protected, virtual, inherited]`

bool itk::Object::PrintObservers	(	std::ostream &	os,
		Indent	indent
	)			const `[protected, inherited]`

template<class TMeasurementVector, class TTargetVector>

virtual void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)			const `[protected, virtual]`

Method to print the object.

Reimplemented from itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >.

virtual void itk::LightObject::PrintTrailer	(	std::ostream &	os,
		Indent	indent
	)			const `[protected, virtual, inherited]`

virtual void itk::DataObject::PropagateRequestedRegion ( ) throw (InvalidRequestedRegionError) [virtual, inherited]

Methods to update the pipeline. Called internally by the pipeline mechanism.

virtual void itk::DataObject::PropagateResetPipeline ( ) [protected, virtual, inherited]

Propagate a call to ResetPipeline(). Called only from ProcessObject.

virtual void itk::Object::Register ( ) const [virtual, inherited]

Increase the reference count (mark as used by another object).

Reimplemented from itk::LightObject.

void itk::DataObject::ReleaseData ( ) [inherited]

Release data back to system to conserve memory resource. Used during pipeline execution. Releasing this data does not make down-stream data invalid, so it does not modify the MTime of this data object.

virtual void itk::DataObject::ReleaseDataFlagOff ( ) [virtual, inherited]

virtual void itk::DataObject::ReleaseDataFlagOn ( ) [virtual, inherited]

void itk::Object::RemoveAllObservers ( ) [inherited]

Remove all observers .

void itk::Object::RemoveObserver ( unsigned long tag ) [inherited]

Remove the observer with this tag value.

virtual bool itk::DataObject::RequestedRegionIsOutsideOfTheBufferedRegion ( ) [inline, virtual, inherited]

Determine whether the RequestedRegion is outside of the BufferedRegion. This method returns true if the RequestedRegion is outside the BufferedRegion (true if at least one pixel is outside). This is used by the pipeline mechanism to determine whether a filter needs to re-execute in order to satisfy the current request. If the current RequestedRegion is already inside the BufferedRegion from the previous execution (and the current filter is up to date), then a given filter does not need to re-execute

Reimplemented in itk::ImageBase< VImageDimension >, itk::PointSet< TPixelType, VDimension, TMeshTraits >, itk::QuadEdgeMesh< TPixel, VDimension, TTraits >, itk::SpatialObject< TDimension >, itk::ImageBase< ::itk::GetImageDimension< itk::VectorImage< TPixelType, Dimension > >::ImageDimension >, itk::ImageBase< ::itk::GetImageDimension< TImage >::ImageDimension >, itk::PointSet< TCoordType, VDimension, itk::DefaultDynamicMeshTraits< TCoordType, 2, 2, TCoordType > >, itk::PointSet< TPixel, VDimension, TTraits >, itk::SpatialObject< 3 >, and itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >.

Definition at line 413 of file itkDataObject.h.

virtual void itk::DataObject::ResetPipeline ( ) [virtual, inherited]

Reset the pipeline. If an exception is thrown during an Update(), the pipeline may be in an inconsistent state. This method clears the internal state of the pipeline so Update() can be called.

void itk::Object::SetDebug ( bool debugFlag ) const [inherited]

Set the value of the debug flag. A non-zero value turns debugging on.

template<class TMeasurementVector, class TTargetVector>

virtual void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetFirstHiddenLayerBias ( ValueType _arg ) [virtual]

template<class TMeasurementVector, class TTargetVector>

void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetFirstHiddenTransferFunction ( TransferFunctionInterfaceType * f )

static void itk::DataObject::SetGlobalReleaseDataFlag ( const bool val ) [static, inherited]

Turn on/off a flag to control whether every object releases its data after being used by a filter. Being a global flag, it controls the behavior of all DataObjects and ProcessObjects.

static void itk::Object::SetGlobalWarningDisplay ( bool flag ) [static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().

template<class TMeasurementVector, class TTargetVector>

void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetInputFunction ( InputFunctionInterfaceType * f )

template<class TMeasurementVector, class TTargetVector>

void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetInputTransferFunction ( TransferFunctionInterfaceType * f )

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

void itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::SetLearningFunction ( LearningFunctionInterfaceType * f ) [inherited]

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

void itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::SetLearningRate ( ValueType learningrate ) [inherited]

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

void itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::SetLearningRule ( LearningFunctionInterfaceType * ) [inherited]

void itk::Object::SetMetaDataDictionary ( const MetaDataDictionary & rhs ) [inherited]

Returns:: Set the MetaDataDictionary

template<class TMeasurementVector, class TTargetVector>

virtual void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetNumOfFirstHiddenNodes ( unsigned int _arg ) [virtual]

template<class TMeasurementVector, class TTargetVector>

virtual void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetNumOfInputNodes ( unsigned int _arg ) [virtual]

template<class TMeasurementVector, class TTargetVector>

virtual void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetNumOfOutputNodes ( unsigned int _arg ) [virtual]

template<class TMeasurementVector, class TTargetVector>

virtual void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetOutputLayerBias ( ValueType _arg ) [virtual]

template<class TMeasurementVector, class TTargetVector>

void itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >::SetOutputTransferFunction ( TransferFunctionInterfaceType * f )

void itk::DataObject::SetPipelineMTime ( unsigned long time ) [inline, inherited]

The maximum MTime of all upstream filters and data objects. This does not include the MTime of this data object.

Definition at line 373 of file itkDataObject.h.

virtual void itk::Object::SetReferenceCount ( int ) [virtual, inherited]

Sets the reference count (use with care)

Reimplemented from itk::LightObject.

void itk::DataObject::SetReleaseDataFlag ( bool flag ) [inline, inherited]

Turn on/off a flag to control whether this object's data is released after being used by a filter.

Definition at line 304 of file itkDataObject.h.

virtual void itk::DataObject::SetRequestedRegion ( DataObject * ) [inline, virtual, inherited]

Set the requested region from this data object to match the requested region of the data object passed in as a parameter. For DataObject's that do not support Regions, this method does nothing. Subclasses of DataObject that do support Regions, provide an alternative implementation.

Definition at line 446 of file itkDataObject.h.

virtual void itk::DataObject::SetRequestedRegionToLargestPossibleRegion ( ) [inline, virtual, inherited]

Set the RequestedRegion to the LargestPossibleRegion. This forces a filter to produce all of the output in one execution (i.e. not streaming) on the next call to Update().

Definition at line 402 of file itkDataObject.h.

bool itk::DataObject::ShouldIReleaseData ( ) const [inherited]

Return flag indicating whether data should be released after use by a filter.

virtual void itk::Object::UnRegister ( ) const [virtual, inherited]

Decrease the reference count (release by another object).

Reimplemented from itk::LightObject.

virtual void itk::DataObject::Update ( ) [virtual, inherited]

Provides opportunity for the data object to insure internal consistency before access. Also causes owning source/filter (if any) to update itself. The Update() method is composed of UpdateOutputInformation(), PropagateRequestedRegion(), and UpdateOutputData(). This method may call methods that throw an InvalidRequestedRegionError exception. This exception will leave the pipeline in an inconsistent state. You will need to call ResetPipeline() on the last ProcessObject in your pipeline in order to restore the pipeline to a state where you can call Update() again.

virtual void itk::DataObject::UpdateOutputData ( ) [virtual, inherited]

Methods to update the pipeline. Called internally by the pipeline mechanism.

virtual void itk::DataObject::UpdateOutputInformation ( ) [virtual, inherited]

Update the information for this DataObject so that it can be used as an output of a ProcessObject. This method is used in the pipeline mechanism to propagate information and initialize the meta data associated with a DataObject. Any implementation of this method in a derived class is assumed to call its source's ProcessObject::UpdateOutputInformation() which determines modified times, LargestPossibleRegions, and any extra meta data like spacing, origin, etc. Default implementation simply call's it's source's UpdateOutputInformation().

template<class TMeasurementVector, class TTargetVector>

virtual void itk::Statistics::NeuralNetworkObject< TMeasurementVector, TTargetVector >::UpdateWeights ( ValueType ) [pure virtual, inherited]

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

virtual void itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::UpdateWeights ( ValueType ) [virtual, inherited]

virtual bool itk::DataObject::VerifyRequestedRegion ( ) [inline, virtual, inherited]

Verify that the RequestedRegion is within the LargestPossibleRegion.

If the RequestedRegion is not within the LargestPossibleRegion, then the filter cannot possibly satisfy the request. This method returns true if the request can be satisfied (even if it will be necessary to process the entire LargestPossibleRegion) and returns false otherwise. This method is used by PropagateRequestedRegion(). PropagateRequestedRegion() throws a InvalidRequestedRegionError exception if the requested region is not within the LargestPossibleRegion. Default implementation simply returns true in order to support DataObjects that do not need regions (for instance itk::EquivalencyTable).

Definition at line 428 of file itkDataObject.h.

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

LayerVectorType itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::m_Layers [protected, inherited]

Definition at line 105 of file itkMultilayerNeuralNetworkBase.h.

Referenced by itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, itk::Statistics::BackPropagationLayer< TMeasurementVector, TTargetVector > >::GetNumOfLayers().

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

LearningFunctionInterfaceType::Pointer itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::m_LearningFunction [protected, inherited]

Definition at line 107 of file itkMultilayerNeuralNetworkBase.h.

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

ValueType itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::m_LearningRate [protected, inherited]

Reimplemented from itk::Statistics::NeuralNetworkObject< TMeasurementVector, TTargetVector >.

Definition at line 108 of file itkMultilayerNeuralNetworkBase.h.

InternalReferenceCountType itk::LightObject::m_ReferenceCount [mutable, protected, inherited]

Number of uses of this object by other objects.

Definition at line 144 of file itkLightObject.h.

SimpleFastMutexLock itk::LightObject::m_ReferenceCountLock [mutable, protected, inherited]

Mutex lock to protect modification to the reference count

Definition at line 147 of file itkLightObject.h.

template<class TMeasurementVector, class TTargetVector, class TLearningLayer = LayerBase<TMeasurementVector, TTargetVector>>

WeightVectorType itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >::m_Weights [protected, inherited]

Definition at line 106 of file itkMultilayerNeuralNetworkBase.h.

Referenced by itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, itk::Statistics::BackPropagationLayer< TMeasurementVector, TTargetVector > >::GetNumOfWeightSets(), and itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, itk::Statistics::BackPropagationLayer< TMeasurementVector, TTargetVector > >::GetWeightSet().

itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector > Class Template Reference

Detailed Description

template<class TMeasurementVector, class TTargetVector>
class itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >

Public Types

Public Member Functions

Static Public Member Functions

Protected Types

Protected Member Functions

Protected Attributes

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation


void	GlobalReleaseDataFlagOff ()
void	GlobalReleaseDataFlagOn ()
static bool	GetGlobalReleaseDataFlag ()
static void	SetGlobalReleaseDataFlag (const bool val)
Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef Superclass::InputFunctionInterfaceType	InputFunctionInterfaceType
typedef Superclass::LayerInterfaceType	LayerInterfaceType
typedef Superclass::LayerVectorType	LayerVectorType
typedef LearningFunctionBase< typename TLearningLayer::LayerInterfaceType, TTargetVector >	LearningFunctionInterfaceType
typedef Superclass::LearningLayerType	LearningLayerType
typedef Superclass::MeasurementVectorType	MeasurementVectorType
typedef Superclass::NetworkOutputType	NetworkOutputType
typedef SmartPointer< Self >	Pointer
typedef OneHiddenLayerBackPropagationNeuralNetwork	Self
typedef MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, BackPropagationLayer< TMeasurementVector, TTargetVector > >	Superclass
typedef Superclass::TargetVectorType	TargetVectorType
typedef Superclass::TransferFunctionInterfaceType	TransferFunctionInterfaceType
typedef Superclass::ValueType	ValueType
typedef Superclass::WeightVectorType	WeightVectorType
Public Member Functions
void	AddLayer (LayerInterfaceType *)
void	AddWeightSet (typename LayerInterfaceType::WeightSetInterfaceType *)
virtual void	BackwardPropagate (NetworkOutputType errors)=0
virtual void	BackwardPropagate (NetworkOutputType errors)
virtual void	CopyInformation (const DataObject *)
virtual LightObject::Pointer	CreateAnother () const
void	DataHasBeenGenerated ()
virtual void	DebugOff () const
virtual void	DebugOn () const
virtual void	Delete ()
void	DisconnectPipeline ()
virtual NetworkOutputType	GenerateOutput (TMeasurementVector samplevector)
Command *	GetCommand (unsigned long tag)
bool	GetDataReleased () const
bool	GetDebug () const
virtual const ValueType &	GetFirstHiddenLayerBias ()
const LayerInterfaceType *	GetLayer (int layer_id) const
LayerInterfaceType *	GetLayer (int layer_id)
const MetaDataDictionary &	GetMetaDataDictionary (void) const
MetaDataDictionary &	GetMetaDataDictionary (void)
virtual unsigned long	GetMTime () const
virtual const char *	GetNameOfClass () const
virtual const unsigned int &	GetNumOfFirstHiddenNodes ()
virtual const unsigned int &	GetNumOfInputNodes ()
int	GetNumOfLayers (void) const
virtual const unsigned int &	GetNumOfOutputNodes ()
int	GetNumOfWeightSets (void) const
virtual const ValueType &	GetOutputLayerBias ()
virtual int	GetReferenceCount () const
SmartPointerForwardReference< ProcessObject >	GetSource () const
unsigned int	GetSourceOutputIndex () const
virtual unsigned long	GetUpdateMTime () const
LayerInterfaceType::WeightSetInterfaceType *	GetWeightSet (unsigned int id)
virtual void	Graft (const DataObject *)
bool	HasObserver (const EventObject &event) const
void	Initialize ()
void	InitializeWeights ()
void	InvokeEvent (const EventObject &) const
void	InvokeEvent (const EventObject &)
virtual void	Modified () const
virtual void	PrepareForNewData ()
void	Print (std::ostream &os, Indent indent=0) const
virtual void	Register () const
void	ReleaseData ()
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
virtual bool	RequestedRegionIsOutsideOfTheBufferedRegion ()
virtual void	ResetPipeline ()
void	SetDebug (bool debugFlag) const
virtual void	SetFirstHiddenLayerBias (ValueType _arg)
void	SetFirstHiddenTransferFunction (TransferFunctionInterfaceType *f)
void	SetInputFunction (InputFunctionInterfaceType *f)
void	SetInputTransferFunction (TransferFunctionInterfaceType *f)
void	SetLearningFunction (LearningFunctionInterfaceType *f)
void	SetLearningRate (ValueType learningrate)
void	SetLearningRule (LearningFunctionInterfaceType *)
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
virtual void	SetNumOfFirstHiddenNodes (unsigned int _arg)
virtual void	SetNumOfInputNodes (unsigned int _arg)
virtual void	SetNumOfOutputNodes (unsigned int _arg)
virtual void	SetOutputLayerBias (ValueType _arg)
void	SetOutputTransferFunction (TransferFunctionInterfaceType *f)
virtual void	SetReferenceCount (int)
virtual void	SetRequestedRegion (DataObject *)
virtual void	SetRequestedRegionToLargestPossibleRegion ()
bool	ShouldIReleaseData () const
virtual void	UnRegister () const
virtual void	Update ()
virtual void	UpdateOutputInformation ()
virtual void	UpdateWeights (ValueType)=0
virtual void	UpdateWeights (ValueType)
virtual bool	VerifyRequestedRegion ()

unsigned long	AddObserver (const EventObject &event, Command *) const
unsigned long	AddObserver (const EventObject &event, Command *)

virtual const unsigned long &	GetPipelineMTime ()
void	SetPipelineMTime (unsigned long time)

virtual const bool &	GetReleaseDataFlag ()
virtual void	ReleaseDataFlagOff ()
virtual void	ReleaseDataFlagOn ()
void	SetReleaseDataFlag (bool flag)

virtual void	PropagateRequestedRegion () throw (InvalidRequestedRegionError)
virtual void	UpdateOutputData ()
Static Public Member Functions
static void	BreakOnError ()
static Pointer	New ()

static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static void	SetGlobalWarningDisplay (bool flag)
Protected Types

typedef int	InternalReferenceCountType
Protected Member Functions
	OneHiddenLayerBackPropagationNeuralNetwork ()
bool	PrintObservers (std::ostream &os, Indent indent) const
virtual void	PrintSelf (std::ostream &os, Indent indent) const
virtual void	PropagateResetPipeline ()
virtual	~OneHiddenLayerBackPropagationNeuralNetwork ()

virtual void	PrintHeader (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const
Protected Attributes
LayerVectorType	m_Layers
LearningFunctionInterfaceType::Pointer	m_LearningFunction
ValueType	m_LearningRate
InternalReferenceCountType	m_ReferenceCount
SimpleFastMutexLock	m_ReferenceCountLock
WeightVectorType	m_Weights

itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector > Class Template Reference

Detailed Description

template<class TMeasurementVector, class TTargetVector> class itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >

Public Types

Public Member Functions

Static Public Member Functions

Protected Types

Protected Member Functions

Protected Attributes

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<class TMeasurementVector, class TTargetVector>
class itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >