gnsstk::CholeskyCrout< T > Class Template Reference

Detailed Description

template<class T>
class gnsstk::CholeskyCrout< T >

Compute the Cholesky decomposition using the Cholesky-Crout algorithm, which is very fast; if A is the given matrix we will get L, where A = L*LT. A must be symetric and positive definite. This is the usual case when A comes from applying a Least Mean-Square (LMS) or Weighted Least Mean-Square (WLMS) method.

NB. U here is NOT the same as U in class Cholesky (but L is the same); here m = transpose(U)*U, but there m = U * transpose(U); see doc for Cholesky.

Definition at line 700 of file MatrixFunctors.hpp.

#include <MatrixFunctors.hpp>

Inheritance diagram for gnsstk::CholeskyCrout< T >:

Public Member Functions
template<class BaseClass >
void	operator() (const ConstMatrixBase< T, BaseClass > &m)
Public Member Functions inherited from gnsstk::Cholesky< T >
template<class BaseClass2 >
void	backSub (RefVectorBase< T, BaseClass2 > &b) const
	Cholesky ()
template<class BaseClass >
void	operator() (const ConstMatrixBase< T, BaseClass > &m)

Additional Inherited Members
Public Attributes inherited from gnsstk::Cholesky< T >
Matrix< T >	L
	Lower triangular and Upper triangular Cholesky decompositions. More...
Matrix< T >	U

Member Function Documentation

operator()()

template<class T >

template<class BaseClass >

void gnsstk::CholeskyCrout< T >::operator() ( const ConstMatrixBase< T, BaseClass > &  m )

inline

Exceptions

MatrixException

Definition at line 707 of file MatrixFunctors.hpp.

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

• MatrixFunctors.hpp