/usr/include/ITK-4.9/itkRBFNetwork.h is in libinsighttoolkit4-dev 4.9.0-4ubuntu1.
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*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkRBFNetwork_h
#define itkRBFNetwork_h
#include "itkMultilayerNeuralNetworkBase.h"
#include "itkBackPropagationLayer.h"
#include "itkSigmoidTransferFunction.h"
#include "itkLogSigmoidTransferFunction.h"
#include "itkTanSigmoidTransferFunction.h"
#include "itkHardLimitTransferFunction.h"
#include "itkSignedHardLimitTransferFunction.h"
#include "itkGaussianTransferFunction.h"
#include "itkIdentityTransferFunction.h"
#include "itkSumInputFunction.h"
#include "itkSymmetricSigmoidTransferFunction.h"
#include "itkTanHTransferFunction.h"
#include "itkRBFLayer.h"
namespace itk
{
namespace Statistics
{
/** \class RBFNetwork
* \brief This is the itkRBFNetwork class.
*
* \ingroup ITKNeuralNetworks
*/
template<typename TMeasurementVector, typename TTargetVector>
class RBFNetwork :
public MultilayerNeuralNetworkBase<TMeasurementVector, TTargetVector, BackPropagationLayer<TMeasurementVector, TTargetVector> >
{
public:
typedef RBFNetwork Self;
typedef MultilayerNeuralNetworkBase<TMeasurementVector, TTargetVector , BackPropagationLayer<TMeasurementVector, TTargetVector> >
Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
typedef typename Superclass::ValueType ValueType;
typedef typename Superclass::MeasurementVectorType MeasurementVectorType;
typedef typename Superclass::TargetVectorType TargetVectorType;
typedef typename Superclass::NetworkOutputType NetworkOutputType;
typedef typename Superclass::LayerInterfaceType LayerInterfaceType;
typedef typename Superclass::LearningLayerType LearningLayerType;
typedef typename Superclass::WeightVectorType WeightVectorType;
typedef typename Superclass::LayerVectorType LayerVectorType;
typedef typename Superclass::TransferFunctionInterfaceType TransferFunctionInterfaceType;
typedef typename Superclass::InputFunctionInterfaceType InputFunctionInterfaceType;
// Specializations for RBF Networks
typedef Array<ValueType> ArrayType;
typedef EuclideanDistanceMetric<ArrayType> DistanceMetricType;
typedef RadialBasisFunctionBase<ValueType> RBFTransferFunctionType;
typedef RBFLayer<TMeasurementVector, TTargetVector> HiddenLayerType;
itkSetMacro(Classes, unsigned int);
itkGetConstReferenceMacro(Classes, unsigned int);
void SetCenter(TMeasurementVector c);
void SetRadius(ValueType r);
void SetDistanceMetric(DistanceMetricType* f);
void InitializeWeights();
/** Method for creation through the object factory. */
itkTypeMacro(RBFNetwork,
MultilayerNeuralNetworkBase);
itkNewMacro(Self);
//Add the layers to the network.
// 1 input, 1 hidden, 1 output
void Initialize() ITK_OVERRIDE;
itkSetMacro(NumOfInputNodes, unsigned int);
itkGetConstReferenceMacro(NumOfInputNodes, unsigned int);
itkSetMacro(NumOfFirstHiddenNodes, unsigned int);
itkGetConstReferenceMacro(NumOfFirstHiddenNodes, unsigned int);
itkSetMacro(NumOfOutputNodes, unsigned int);
itkGetConstReferenceMacro(NumOfOutputNodes, unsigned int);
itkSetMacro(FirstHiddenLayerBias, ValueType);
itkGetConstReferenceMacro(FirstHiddenLayerBias, ValueType);
//#define __USE_OLD_INTERFACE Comment out to ensure that new interface works
#ifdef __USE_OLD_INTERFACE
//Original Function name before consistency naming changes
inline void SetNumOfHiddenNodes(const unsigned int & x) { SetNumOfFirstHiddenNodes(x); }
inline unsigned int GetNumOfHiddenNodes(void) const { return GetNumOfFirstHiddenNodes(); }
inline void SetHiddenLayerBias(const ValueType & bias) { SetFirstHiddenLayerBias(bias); }
ValueType GetHiddenLayerBias(void) const { return GetFirstHiddenLayerBias();}
#endif
itkSetMacro(OutputLayerBias, ValueType);
itkGetConstReferenceMacro(OutputLayerBias, ValueType);
virtual NetworkOutputType GenerateOutput(TMeasurementVector samplevector) ITK_OVERRIDE;
void SetInputFunction(InputFunctionInterfaceType* f);
void SetInputTransferFunction(TransferFunctionInterfaceType* f);
#ifdef __USE_OLD_INTERFACE
//Original Function name before consistency naming changes
inline void SetHiddenTransferFunction(TransferFunctionInterfaceType* f) { SetFirstHiddenTransferFunction (f); }
#endif
void SetFirstHiddenTransferFunction(TransferFunctionInterfaceType* f);
void SetOutputTransferFunction(TransferFunctionInterfaceType* f);
protected:
RBFNetwork();
virtual ~RBFNetwork(){};
/** Method to print the object. */
virtual void PrintSelf( std::ostream& os, Indent indent ) const ITK_OVERRIDE;
private:
typename DistanceMetricType::Pointer m_DistanceMetric;
std::vector<TMeasurementVector> m_Centers; // ui....uc
std::vector<double> m_Radii;
unsigned int m_Classes;
unsigned int m_NumOfInputNodes;
unsigned int m_NumOfFirstHiddenNodes;
unsigned int m_NumOfOutputNodes;
ValueType m_FirstHiddenLayerBias;
ValueType m_OutputLayerBias;
typename InputFunctionInterfaceType::Pointer m_InputFunction;
typename TransferFunctionInterfaceType::Pointer m_InputTransferFunction;
typename RBFTransferFunctionType::Pointer m_FirstHiddenTransferFunction;
typename TransferFunctionInterfaceType::Pointer m_OutputTransferFunction;
};
} // end namespace Statistics
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkRBFNetwork.hxx"
#endif
#endif
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