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/home/abuild/rpmbuild/BUILD/lapack-3.12.0/SRC/DEPRECATED/zggsvd.f(3) Library Functions Manual /home/abuild/rpmbuild/BUILD/lapack-3.12.0/SRC/DEPRECATED/zggsvd.f(3)

NAME

/home/abuild/rpmbuild/BUILD/lapack-3.12.0/SRC/DEPRECATED/zggsvd.f

SYNOPSIS

Functions/Subroutines


subroutine ZGGSVD (jobu, jobv, jobq, m, n, p, k, l, a, lda, b, ldb, alpha, beta, u, ldu, v, ldv, q, ldq, work, rwork, iwork, info)
ZGGSVD computes the singular value decomposition (SVD) for OTHER matrices

Function/Subroutine Documentation

subroutine ZGGSVD (character jobu, character jobv, character jobq, integer m, integer n, integer p, integer k, integer l, complex*16, dimension( lda, * ) a, integer lda, complex*16, dimension( ldb, * ) b, integer ldb, double precision, dimension( * ) alpha, double precision, dimension( * ) beta, complex*16, dimension( ldu, * ) u, integer ldu, complex*16, dimension( ldv, * ) v, integer ldv, complex*16, dimension( ldq, * ) q, integer ldq, complex*16, dimension( * ) work, double precision, dimension( * ) rwork, integer, dimension( * ) iwork, integer info)

ZGGSVD computes the singular value decomposition (SVD) for OTHER matrices

Purpose:

!>
!> This routine is deprecated and has been replaced by routine ZGGSVD3.
!>
!> ZGGSVD computes the generalized singular value decomposition (GSVD)
!> of an M-by-N complex matrix A and P-by-N complex matrix B:
!>
!>       U**H*A*Q = D1*( 0 R ),    V**H*B*Q = D2*( 0 R )
!>
!> where U, V and Q are unitary matrices.
!> Let K+L = the effective numerical rank of the
!> matrix (A**H,B**H)**H, then R is a (K+L)-by-(K+L) nonsingular upper
!> triangular matrix, D1 and D2 are M-by-(K+L) and P-by-(K+L) 
!> matrices and of the following structures, respectively:
!>
!> If M-K-L >= 0,
!>
!>                     K  L
!>        D1 =     K ( I  0 )
!>                 L ( 0  C )
!>             M-K-L ( 0  0 )
!>
!>                   K  L
!>        D2 =   L ( 0  S )
!>             P-L ( 0  0 )
!>
!>                 N-K-L  K    L
!>   ( 0 R ) = K (  0   R11  R12 )
!>             L (  0    0   R22 )
!> where
!>
!>   C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
!>   S = diag( BETA(K+1),  ... , BETA(K+L) ),
!>   C**2 + S**2 = I.
!>
!>   R is stored in A(1:K+L,N-K-L+1:N) on exit.
!>
!> If M-K-L < 0,
!>
!>                   K M-K K+L-M
!>        D1 =   K ( I  0    0   )
!>             M-K ( 0  C    0   )
!>
!>                     K M-K K+L-M
!>        D2 =   M-K ( 0  S    0  )
!>             K+L-M ( 0  0    I  )
!>               P-L ( 0  0    0  )
!>
!>                    N-K-L  K   M-K  K+L-M
!>   ( 0 R ) =     K ( 0    R11  R12  R13  )
!>               M-K ( 0     0   R22  R23  )
!>             K+L-M ( 0     0    0   R33  )
!>
!> where
!>
!>   C = diag( ALPHA(K+1), ... , ALPHA(M) ),
!>   S = diag( BETA(K+1),  ... , BETA(M) ),
!>   C**2 + S**2 = I.
!>
!>   (R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N), and R33 is stored
!>   ( 0  R22 R23 )
!>   in B(M-K+1:L,N+M-K-L+1:N) on exit.
!>
!> The routine computes C, S, R, and optionally the unitary
!> transformation matrices U, V and Q.
!>
!> In particular, if B is an N-by-N nonsingular matrix, then the GSVD of
!> A and B implicitly gives the SVD of A*inv(B):
!>                      A*inv(B) = U*(D1*inv(D2))*V**H.
!> If ( A**H,B**H)**H has orthonormal columns, then the GSVD of A and B is also
!> equal to the CS decomposition of A and B. Furthermore, the GSVD can
!> be used to derive the solution of the eigenvalue problem:
!>                      A**H*A x = lambda* B**H*B x.
!> In some literature, the GSVD of A and B is presented in the form
!>                  U**H*A*X = ( 0 D1 ),   V**H*B*X = ( 0 D2 )
!> where U and V are orthogonal and X is nonsingular, and D1 and D2 are
!> ``diagonal''.  The former GSVD form can be converted to the latter
!> form by taking the nonsingular matrix X as
!>
!>                       X = Q*(  I   0    )
!>                             (  0 inv(R) )
!> 

Parameters

JOBU

!>          JOBU is CHARACTER*1
!>          = 'U':  Unitary matrix U is computed;
!>          = 'N':  U is not computed.
!> 

JOBV

!>          JOBV is CHARACTER*1
!>          = 'V':  Unitary matrix V is computed;
!>          = 'N':  V is not computed.
!> 

JOBQ

!>          JOBQ is CHARACTER*1
!>          = 'Q':  Unitary matrix Q is computed;
!>          = 'N':  Q is not computed.
!> 

M

!>          M is INTEGER
!>          The number of rows of the matrix A.  M >= 0.
!> 

N

!>          N is INTEGER
!>          The number of columns of the matrices A and B.  N >= 0.
!> 

P

!>          P is INTEGER
!>          The number of rows of the matrix B.  P >= 0.
!> 

K

!>          K is INTEGER
!> 

L

!>          L is INTEGER
!>
!>          On exit, K and L specify the dimension of the subblocks
!>          described in Purpose.
!>          K + L = effective numerical rank of (A**H,B**H)**H.
!> 

A

!>          A is COMPLEX*16 array, dimension (LDA,N)
!>          On entry, the M-by-N matrix A.
!>          On exit, A contains the triangular matrix R, or part of R.
!>          See Purpose for details.
!> 

LDA

!>          LDA is INTEGER
!>          The leading dimension of the array A. LDA >= max(1,M).
!> 

B

!>          B is COMPLEX*16 array, dimension (LDB,N)
!>          On entry, the P-by-N matrix B.
!>          On exit, B contains part of the triangular matrix R if
!>          M-K-L < 0.  See Purpose for details.
!> 

LDB

!>          LDB is INTEGER
!>          The leading dimension of the array B. LDB >= max(1,P).
!> 

ALPHA

!>          ALPHA is DOUBLE PRECISION array, dimension (N)
!> 

BETA

!>          BETA is DOUBLE PRECISION array, dimension (N)
!>
!>          On exit, ALPHA and BETA contain the generalized singular
!>          value pairs of A and B;
!>            ALPHA(1:K) = 1,
!>            BETA(1:K)  = 0,
!>          and if M-K-L >= 0,
!>            ALPHA(K+1:K+L) = C,
!>            BETA(K+1:K+L)  = S,
!>          or if M-K-L < 0,
!>            ALPHA(K+1:M)=C, ALPHA(M+1:K+L)=0
!>            BETA(K+1:M) =S, BETA(M+1:K+L) =1
!>          and
!>            ALPHA(K+L+1:N) = 0
!>            BETA(K+L+1:N)  = 0
!> 

U

!>          U is COMPLEX*16 array, dimension (LDU,M)
!>          If JOBU = 'U', U contains the M-by-M unitary matrix U.
!>          If JOBU = 'N', U is not referenced.
!> 

LDU

!>          LDU is INTEGER
!>          The leading dimension of the array U. LDU >= max(1,M) if
!>          JOBU = 'U'; LDU >= 1 otherwise.
!> 

V

!>          V is COMPLEX*16 array, dimension (LDV,P)
!>          If JOBV = 'V', V contains the P-by-P unitary matrix V.
!>          If JOBV = 'N', V is not referenced.
!> 

LDV

!>          LDV is INTEGER
!>          The leading dimension of the array V. LDV >= max(1,P) if
!>          JOBV = 'V'; LDV >= 1 otherwise.
!> 

Q

!>          Q is COMPLEX*16 array, dimension (LDQ,N)
!>          If JOBQ = 'Q', Q contains the N-by-N unitary matrix Q.
!>          If JOBQ = 'N', Q is not referenced.
!> 

LDQ

!>          LDQ is INTEGER
!>          The leading dimension of the array Q. LDQ >= max(1,N) if
!>          JOBQ = 'Q'; LDQ >= 1 otherwise.
!> 

WORK

!>          WORK is COMPLEX*16 array, dimension (max(3*N,M,P)+N)
!> 

RWORK

!>          RWORK is DOUBLE PRECISION array, dimension (2*N)
!> 

IWORK

!>          IWORK is INTEGER array, dimension (N)
!>          On exit, IWORK stores the sorting information. More
!>          precisely, the following loop will sort ALPHA
!>             for I = K+1, min(M,K+L)
!>                 swap ALPHA(I) and ALPHA(IWORK(I))
!>             endfor
!>          such that ALPHA(1) >= ALPHA(2) >= ... >= ALPHA(N).
!> 

INFO

!>          INFO is INTEGER
!>          = 0:  successful exit.
!>          < 0:  if INFO = -i, the i-th argument had an illegal value.
!>          > 0:  if INFO = 1, the Jacobi-type procedure failed to
!>                converge.  For further details, see subroutine ZTGSJA.
!> 

Internal Parameters:

!>  TOLA    DOUBLE PRECISION
!>  TOLB    DOUBLE PRECISION
!>          TOLA and TOLB are the thresholds to determine the effective
!>          rank of (A**H,B**H)**H. Generally, they are set to
!>                   TOLA = MAX(M,N)*norm(A)*MAZHEPS,
!>                   TOLB = MAX(P,N)*norm(B)*MAZHEPS.
!>          The size of TOLA and TOLB may affect the size of backward
!>          errors of the decomposition.
!> 

Author

Univ. of Tennessee

Univ. of California Berkeley

Univ. of Colorado Denver

NAG Ltd.

Contributors:

Ming Gu and Huan Ren, Computer Science Division, University of California at Berkeley, USA

Definition at line 334 of file zggsvd.f.

Author

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Version 3.12.0 LAPACK