slasq6 (l) - Linux Manuals
slasq6: computes one dqd (shift equal to zero) transform in ping-pong form, with protection against underflow and overflow
Command to display slasq6
manual in Linux: $ man l slasq6
NAME
SLASQ6 - computes one dqd (shift equal to zero) transform in ping-pong form, with protection against underflow and overflow
SYNOPSIS
- SUBROUTINE SLASQ6(
-
I0, N0, Z, PP, DMIN, DMIN1, DMIN2, DN,
DNM1, DNM2 )
-
INTEGER
I0, N0, PP
-
REAL
DMIN, DMIN1, DMIN2, DN, DNM1, DNM2
-
REAL
Z( * )
PURPOSE
SLASQ6 computes one dqd (shift equal to zero) transform in
ping-pong form, with protection against underflow and overflow.
ARGUMENTS
- I0 (input) INTEGER
-
First index.
- N0 (input) INTEGER
-
Last index.
- Z (input) REAL array, dimension ( 4*N )
-
Z holds the qd array. EMIN is stored in Z(4*N0) to avoid
an extra argument.
- PP (input) INTEGER
-
PP=0 for ping, PP=1 for pong.
- DMIN (output) REAL
-
Minimum value of d.
DMIN1 (output) REAL
Minimum value of d, excluding D( N0 ).
DMIN2 (output) REAL
Minimum value of d, excluding D( N0 ) and D( N0-1 ).
- DN (output) REAL
-
d(N0), the last value of d.
- DNM1 (output) REAL
-
d(N0-1).
- DNM2 (output) REAL
-
d(N0-2).
Pages related to slasq6
- slasq6 (3)
- slasq1 (l) - computes the singular values of a real N-by-N bidiagonal matrix with diagonal D and off-diagonal E
- slasq2 (l) - computes all the eigenvalues of the symmetric positive definite tridiagonal matrix associated with the qd array Z to high relative accuracy are computed to high relative accuracy, in the absence of denormalization, underflow and overflow
- slasq3 (l) - checks for deflation, computes a shift (TAU) and calls dqds
- slasq4 (l) - computes an approximation TAU to the smallest eigenvalue using values of d from the previous transform
- slasq5 (l) - computes one dqds transform in ping-pong form, one version for IEEE machines another for non IEEE machines
- slas2 (l) - computes the singular values of the 2-by-2 matrix [ F G ] [ 0 H ]
- slascl (l) - multiplies the M by N real matrix A by the real scalar CTO/CFROM
- slascl2 (l) - performs a diagonal scaling on a vector
- slasd0 (l) - a divide and conquer approach, SLASD0 computes the singular value decomposition (SVD) of a real upper bidiagonal N-by-M matrix B with diagonal D and offdiagonal E, where M = N + SQRE