クラス rcsc::NGNet

Normalized Gaussian Radial Basis Function Network [詳細]

#include <ngnet.h>

すべてのメンバ一覧

Public 型

enum  { INPUT = 2 }
enum  { OUTPUT = 2 }
typedef boost::array< double,
INPUT > 
input_vector
 typedef of the input array type that uses fixed size
typedef boost::array< double,
OUTPUT > 
output_vector
 typedef of the output array type that uses fixed size

Public メソッド

 NGNet ()
 initialize member variables
void setLearningRate (const double &eta, const double &alpha)
 assign learning parameters
void setWeightRange (const double &min_weight, const double &max_weight)
 assign the range of the network connection weight
void setInitialSigma (const double &initial_sigma)
 assign the initial sigma value
const std::vector< Unit > & units () const
 get the unit container
void addCenter (const input_vector &center)
 add new center point
void propagate (const input_vector &input, output_vector &output) const
 calculate the output of this network
double train (const input_vector &input, const output_vector &teacher)
 train this network with teacher signal
bool read (std::istream &is)
 load network structure from input stream
std::ostream & print (std::ostream &os) const
 print network structor
std::ostream & printUnits (std::ostream &os) const
 print all units, not network connection weights

構成

struct  Unit
 radial basis function unit [詳細]


説明

Normalized Gaussian Radial Basis Function Network


関数

void rcsc::NGNet::setLearningRate ( const double &  eta,
const double &  alpha 
) [inline]

assign learning parameters

引数:
eta new learning parameter
alpha new learning parameter

void rcsc::NGNet::setWeightRange ( const double &  min_weight,
const double &  max_weight 
) [inline]

assign the range of the network connection weight

引数:
min_weight minimum weight
max_weight maximum weight

void rcsc::NGNet::setInitialSigma ( const double &  initial_sigma  )  [inline]

assign the initial sigma value

引数:
initial_sigma sigma value

const std::vector< Unit >& rcsc::NGNet::units (  )  const [inline]

get the unit container

戻り値:
const reference to the unit container

void rcsc::NGNet::addCenter ( const input_vector center  ) 

add new center point

引数:
center new center point

void rcsc::NGNet::propagate ( const input_vector input,
output_vector output 
) const

calculate the output of this network

引数:
input input value
output reference to the result variable

double rcsc::NGNet::train ( const input_vector input,
const output_vector teacher 
)

train this network with teacher signal

引数:
input input value
teacher teacher output value
戻り値:
sum of the squared error value

bool rcsc::NGNet::read ( std::istream &  is  ) 

load network structure from input stream

引数:
is reference to the input stream
戻り値:
true if successfully read

std::ostream & rcsc::NGNet::print ( std::ostream &  os  )  const

print network structor

引数:
os reference to the output stream
戻り値:
reference to the output stream

std::ostream & rcsc::NGNet::printUnits ( std::ostream &  os  )  const

print all units, not network connection weights

引数:
os reference to the output stream
戻り値:
reference to the output stream


このクラスの説明は次のファイルから生成されました:
librcscに対してThu May 1 15:41:24 2008に生成されました。  doxygen 1.5.0