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JAMA::SVD Class Template Reference

`#include <jama_svd.h>`

List of all members.

Public Methods

SVD (const Array2D< Real > &Arg)
void getU (Array2D< Real > &A)
void getV (Array2D< Real > &A)
void getSingularValues (Array1D< Real > &x)
void getS (Array2D< Real > &A)
double norm2 ()
double cond ()
int rank ()

Detailed Description

template<class Real> class JAMA::SVD

Singular Value Decomposition.

For an m-by-n matrix A with m >= n, the singular value decomposition is an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and an n-by-n orthogonal matrix V so that A = U*S*V'.

The singular values, sigma[k] = S[k][k], are ordered so that sigma[0] >= sigma[1] >= ... >= sigma[n-1].

The singular value decompostion always exists, so the constructor will never fail. The matrix condition number and the effective numerical rank can be computed from this decomposition.

(Adapted from JAMA, a Java Matrix Library, developed by jointly by the Mathworks and NIST; see http://math.nist.gov/javanumerics/jama).

Constructor & Destructor Documentation

 template JAMA::SVD::SVD ( const Array2D< Real > & Arg )` [inline]`

Member Function Documentation

 template double JAMA::SVD::cond ( )` [inline]`
 Two norm of condition number (max(S)/min(S))

 template void JAMA::SVD::getS ( Array2D< Real > & A )` [inline]`
 Return the diagonal matrix of singular values Returns: S

 template void JAMA::SVD::getSingularValues ( Array1D< Real > & x )` [inline]`
 Return the one-dimensional array of singular values

 template void JAMA::SVD::getU ( Array2D< Real > & A )` [inline]`

 template void JAMA::SVD::getV ( Array2D< Real > & A )` [inline]`

 template double JAMA::SVD::norm2 ( )` [inline]`
 Two norm (max(S))

 template int JAMA::SVD::rank ( )` [inline]`
 Effective numerical matrix rank Returns: Number of nonnegligible singular values.

The documentation for this class was generated from the following file:
Generated at Mon Jan 20 07:47:18 2003 for JAMA/C++ by 1.2.5 written by Dimitri van Heesch, © 1997-2001