openModeller  Version 1.5.0
Public Member Functions | Public Attributes | List of all members
Network Class Reference

#include <nn.h>

Collaboration diagram for Network:
Collaboration graph

Public Member Functions

 Network ()
 
int SetData (double learning_rate, int layers[], int tot_layers)
 
void SetInputs (vector< double > inputs) const
 
void RandomizeWB (void)
 
double * GetOutput (void) const
 
double getWeight (int i, int j, int k) const
 
void setWeight (int i, int j, int k, double w)
 
double getBias (int i, int j) const
 
void setBias (int i, int j, double b)
 
void Update (void)
 
double Limiter (double value) const
 
double GetRand (void)
 
double SigmaWeightDelta (unsigned long layer_no, unsigned long neuron_no)
 
void setError (int max_pattern)
 
void addError (int max_pattern)
 
int Train (vector< double > inputs, vector< double > outputs, int number_pattern, int max_pattern, double momentum)
 
void trainingEpoch (unsigned long actual_epoch, double epoch_total, int patterns)
 
int trainingMinimumError (int patterns, double min_error)
 
float getProgress ()
 
 ~Network ()
 

Public Attributes

double net_learning_rate
 
Layer * Layers
 
int net_tot_layers
 
double * net_inputs
 
double * net_outputs
 
int * net_layers
 
double * square_error
 
double * mean_square_error
 
float progress
 

Detailed Description

Definition at line 151 of file nn.h.

Constructor & Destructor Documentation

Network::Network ( )
inline

Definition at line 168 of file nn.h.

Network::~Network ( )
inline

Definition at line 549 of file nn.h.

Member Function Documentation

void Network::addError ( int  max_pattern)
inline

Definition at line 397 of file nn.h.

References mean_square_error, and square_error.

Referenced by Train().

double Network::getBias ( int  i,
int  j 
) const
inline

Definition at line 293 of file nn.h.

References Layers, Neuron::n_bias, and Layer::Neurons.

Referenced by NNAlgorithm::_getConfiguration().

double* Network::GetOutput ( void  ) const
inline

Definition at line 243 of file nn.h.

References Dendrite::d_weight, Neuron::Dendrites, Layers, Limiter(), Neuron::n_bias, Neuron::n_value, net_layers, net_tot_layers, and Layer::Neurons.

Referenced by NNAlgorithm::getValue(), and Update().

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float Network::getProgress ( )
inline

Definition at line 542 of file nn.h.

References progress.

Referenced by NNAlgorithm::iterate().

double Network::GetRand ( void  )
inline

Definition at line 331 of file nn.h.

References RANDOM_CLAMP, and RANDOM_NUM.

Referenced by RandomizeWB().

double Network::getWeight ( int  i,
int  j,
int  k 
) const
inline

Definition at line 280 of file nn.h.

References Dendrite::d_weight, Neuron::Dendrites, Layers, and Layer::Neurons.

Referenced by NNAlgorithm::_getConfiguration().

double Network::Limiter ( double  value) const
inline

Definition at line 324 of file nn.h.

Referenced by GetOutput().

void Network::RandomizeWB ( void  )
inline

Definition at line 213 of file nn.h.

References Dendrite::d_weight, Dendrite::d_weight_actual, Dendrite::d_weight_ancient, Neuron::Dendrites, GetRand(), Layers, Neuron::n_bias, net_layers, net_tot_layers, Layer::Neurons, and Neuron::SetDendrites().

Referenced by NNAlgorithm::_setConfiguration(), and NNAlgorithm::initialize().

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void Network::setBias ( int  i,
int  j,
double  b 
)
inline

Definition at line 299 of file nn.h.

References Layers, Neuron::n_bias, and Layer::Neurons.

Referenced by NNAlgorithm::_setConfiguration().

int Network::SetData ( double  learning_rate,
int  layers[],
int  tot_layers 
)
inline

Definition at line 173 of file nn.h.

References Layer::Initialize(), Layers, net_inputs, net_layers, net_learning_rate, net_outputs, and net_tot_layers.

Referenced by NNAlgorithm::_setConfiguration(), and NNAlgorithm::initialize().

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void Network::setError ( int  max_pattern)
inline

Definition at line 383 of file nn.h.

References mean_square_error, and square_error.

Referenced by Train().

void Network::SetInputs ( vector< double >  inputs) const
inline

Definition at line 204 of file nn.h.

References Layers, Neuron::n_value, net_layers, and Layer::Neurons.

Referenced by NNAlgorithm::getValue(), and Train().

void Network::setWeight ( int  i,
int  j,
int  k,
double  w 
)
inline

Definition at line 286 of file nn.h.

References Dendrite::d_weight, Neuron::Dendrites, Layers, and Layer::Neurons.

Referenced by NNAlgorithm::_setConfiguration().

double Network::SigmaWeightDelta ( unsigned long  layer_no,
unsigned long  neuron_no 
)
inline

Definition at line 357 of file nn.h.

References Dendrite::d_weight, Neuron::Dendrites, Layers, Neuron::n_delta, net_layers, and Layer::Neurons.

Referenced by Train().

int Network::Train ( vector< double >  inputs,
vector< double >  outputs,
int  number_pattern,
int  max_pattern,
double  momentum 
)
inline

Definition at line 408 of file nn.h.

References addError(), Dendrite::d_weight, Dendrite::d_weight_actual, Dendrite::d_weight_ancient, Neuron::Dendrites, error, Layers, Neuron::n_bias, Neuron::n_delta, Neuron::n_value, net_layers, net_learning_rate, net_tot_layers, Layer::Neurons, setError(), SetInputs(), SigmaWeightDelta(), square_error, and Update().

Referenced by NNAlgorithm::iterate().

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void Network::trainingEpoch ( unsigned long  actual_epoch,
double  epoch_total,
int  patterns 
)
inline

Definition at line 504 of file nn.h.

References mean_square_error, and progress.

Referenced by NNAlgorithm::iterate().

int Network::trainingMinimumError ( int  patterns,
double  min_error 
)
inline

Definition at line 516 of file nn.h.

References mean_square_error, and progress.

Referenced by NNAlgorithm::iterate().

void Network::Update ( void  )
inline

Definition at line 306 of file nn.h.

References GetOutput().

Referenced by Train().

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Member Data Documentation

Layer* Network::Layers

Definition at line 156 of file nn.h.

Referenced by getBias(), GetOutput(), getWeight(), RandomizeWB(), setBias(), SetData(), SetInputs(), setWeight(), SigmaWeightDelta(), and Train().

double* Network::mean_square_error

Definition at line 164 of file nn.h.

Referenced by addError(), setError(), trainingEpoch(), and trainingMinimumError().

double* Network::net_inputs

Definition at line 158 of file nn.h.

Referenced by SetData().

int* Network::net_layers

Definition at line 160 of file nn.h.

Referenced by GetOutput(), RandomizeWB(), SetData(), SetInputs(), SigmaWeightDelta(), and Train().

double Network::net_learning_rate

Definition at line 155 of file nn.h.

Referenced by SetData(), and Train().

double* Network::net_outputs

Definition at line 159 of file nn.h.

Referenced by SetData().

int Network::net_tot_layers

Definition at line 157 of file nn.h.

Referenced by GetOutput(), RandomizeWB(), SetData(), and Train().

float Network::progress

Definition at line 166 of file nn.h.

Referenced by getProgress(), trainingEpoch(), and trainingMinimumError().

double* Network::square_error

Definition at line 163 of file nn.h.

Referenced by addError(), setError(), and Train().

The documentation for this class was generated from the following file: