GESVD: computes the singular value decomposition (SVD) of a complex M-by-N matrix A, optionally computing the left and/or right singular vectors. The SVD is written A = U * SIGMA * conjugate-transpose(V) where SIGMA is an M-by-N matrix which is zero except for its min(m,n) diagonal elements, U is an M-by-M unitary matrix, and V is an N-by-N unitary matrix. The diagonal elements of SIGMA are the singular values of A; they are real and non-negative, and are returned in descending order. The first min(m,n) columns of U and V are the left and right singular vectors of A. Note that the routine returns V**H, not V. More...

Public Member Functions
	la_cgesvd

	la_dgesvd

	la_qgesvd

	la_sgesvd

	la_wgesvd

	la_zgesvd

Detailed Description

GESVD: computes the singular value decomposition (SVD) of a complex M-by-N matrix A, optionally computing the left and/or right singular vectors. The SVD is written A = U * SIGMA * conjugate-transpose(V) where SIGMA is an M-by-N matrix which is zero except for its min(m,n) diagonal elements, U is an M-by-M unitary matrix, and V is an N-by-N unitary matrix. The diagonal elements of SIGMA are the singular values of A; they are real and non-negative, and are returned in descending order. The first min(m,n) columns of U and V are the left and right singular vectors of A. Note that the routine returns V**H, not V.

Member Function/Subroutine Documentation

◆ la_cgesvd()

la_lapack::gesvd::la_cgesvd

◆ la_dgesvd()

la_lapack::gesvd::la_dgesvd

◆ la_qgesvd()

la_lapack::gesvd::la_qgesvd

◆ la_sgesvd()

la_lapack::gesvd::la_sgesvd

◆ la_wgesvd()

la_lapack::gesvd::la_wgesvd

◆ la_zgesvd()

la_lapack::gesvd::la_zgesvd

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

la_lapack.F90

Public Member Functions