Generalized Singular Value Decomposition:
LAPACK Computational Routines
This
topic
describes LAPACK computational routines used for finding the
generalized singular value decomposition (GSVD) of two matrices
A
and
B
as
U
H
AQ
=
D
1
*(0
R
)V
H
BQ
=
D
2
*(0
R
)where
U
,
V
, and
Q
are
orthogonal/unitary matrices,
R
is a
nonsingular upper triangular matrix, and
D
1
,
D
2
are “diagonal” matrices of the structure
detailed in the routines description section.
Table
“Computational Routines for Generalized
Singular Value Decomposition”
lists LAPACK routines
that perform generalized singular value decomposition of matrices.
You can use routines listed in the above table as well
as the driver routine
ggsvd to find the GSVD of
a pair of general rectangular matrices.