Linux and UNIX Man Pages

Linux & Unix Commands - Search Man Pages

dlasv2(l) [redhat man page]

DLASV2(l)								 )								 DLASV2(l)

NAME
DLASV2 - compute the singular value decomposition of a 2-by-2 triangular matrix [ F G ] [ 0 H ] SYNOPSIS
SUBROUTINE DLASV2( F, G, H, SSMIN, SSMAX, SNR, CSR, SNL, CSL ) DOUBLE PRECISION CSL, CSR, F, G, H, SNL, SNR, SSMAX, SSMIN PURPOSE
DLASV2 computes the singular value decomposition of a 2-by-2 triangular matrix [ F G ] [ 0 H ]. On return, abs(SSMAX) is the larger singu- lar value, abs(SSMIN) is the smaller singular value, and (CSL,SNL) and (CSR,SNR) are the left and right singular vectors for abs(SSMAX), giving the decomposition [ CSL SNL ] [ F G ] [ CSR -SNR ] = [ SSMAX 0 ] [-SNL CSL ] [ 0 H ] [ SNR CSR ] [ 0 SSMIN ]. ARGUMENTS
F (input) DOUBLE PRECISION The (1,1) element of the 2-by-2 matrix. G (input) DOUBLE PRECISION The (1,2) element of the 2-by-2 matrix. H (input) DOUBLE PRECISION The (2,2) element of the 2-by-2 matrix. SSMIN (output) DOUBLE PRECISION abs(SSMIN) is the smaller singular value. SSMAX (output) DOUBLE PRECISION abs(SSMAX) is the larger singular value. SNL (output) DOUBLE PRECISION CSL (output) DOUBLE PRECISION The vector (CSL, SNL) is a unit left singular vector for the singular value abs(SSMAX). SNR (output) DOUBLE PRECISION CSR (output) DOUBLE PRECISION The vector (CSR, SNR) is a unit right singular vector for the singular value abs(SSMAX). FURTHER DETAILS
Any input parameter may be aliased with any output parameter. Barring over/underflow and assuming a guard digit in subtraction, all output quantities are correct to within a few units in the last place (ulps). In IEEE arithmetic, the code works correctly if one matrix element is infinite. Overflow will not occur unless the largest singular value itself overflows or is within a few ulps of overflow. (On machines with partial overflow, like the Cray, overflow may occur if the largest singular value is within a factor of 2 of overflow.) Underflow is harmless if underflow is gradual. Otherwise, results may correspond to a matrix modified by perturbations of size near the underflow threshold. LAPACK version 3.0 15 June 2000 DLASV2(l)

Check Out this Related Man Page

dlasv2.f(3)							      LAPACK							       dlasv2.f(3)

NAME
dlasv2.f - SYNOPSIS
Functions/Subroutines subroutine dlasv2 (F, G, H, SSMIN, SSMAX, SNR, CSR, SNL, CSL) DLASV2 computes the singular value decomposition of a 2-by-2 triangular matrix. Function/Subroutine Documentation subroutine dlasv2 (double precisionF, double precisionG, double precisionH, double precisionSSMIN, double precisionSSMAX, double precisionSNR, double precisionCSR, double precisionSNL, double precisionCSL) DLASV2 computes the singular value decomposition of a 2-by-2 triangular matrix. Purpose: DLASV2 computes the singular value decomposition of a 2-by-2 triangular matrix [ F G ] [ 0 H ]. On return, abs(SSMAX) is the larger singular value, abs(SSMIN) is the smaller singular value, and (CSL,SNL) and (CSR,SNR) are the left and right singular vectors for abs(SSMAX), giving the decomposition [ CSL SNL ] [ F G ] [ CSR -SNR ] = [ SSMAX 0 ] [-SNL CSL ] [ 0 H ] [ SNR CSR ] [ 0 SSMIN ]. Parameters: F F is DOUBLE PRECISION The (1,1) element of the 2-by-2 matrix. G G is DOUBLE PRECISION The (1,2) element of the 2-by-2 matrix. H H is DOUBLE PRECISION The (2,2) element of the 2-by-2 matrix. SSMIN SSMIN is DOUBLE PRECISION abs(SSMIN) is the smaller singular value. SSMAX SSMAX is DOUBLE PRECISION abs(SSMAX) is the larger singular value. SNL SNL is DOUBLE PRECISION CSL CSL is DOUBLE PRECISION The vector (CSL, SNL) is a unit left singular vector for the singular value abs(SSMAX). SNR SNR is DOUBLE PRECISION CSR CSR is DOUBLE PRECISION The vector (CSR, SNR) is a unit right singular vector for the singular value abs(SSMAX). Author: Univ. of Tennessee Univ. of California Berkeley Univ. of Colorado Denver NAG Ltd. Date: September 2012 Further Details: Any input parameter may be aliased with any output parameter. Barring over/underflow and assuming a guard digit in subtraction, all output quantities are correct to within a few units in the last place (ulps). In IEEE arithmetic, the code works correctly if one matrix element is infinite. Overflow will not occur unless the largest singular value itself overflows or is within a few ulps of overflow. (On machines with partial overflow, like the Cray, overflow may occur if the largest singular value is within a factor of 2 of overflow.) Underflow is harmless if underflow is gradual. Otherwise, results may correspond to a matrix modified by perturbations of size near the underflow threshold. Definition at line 139 of file dlasv2.f. Author Generated automatically by Doxygen for LAPACK from the source code. Version 3.4.2 Tue Sep 25 2012 dlasv2.f(3)
Man Page