SRC/DEPRECATED/cggsvd.f(3)

NAME
SRC/DEPRECATED/cggsvd.f

SYNOPSIS

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

Function/Subroutine Documentation

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

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

Purpose:

    !>
    !> This routine is deprecated and has been replaced by routine CGGSVD3.
    !>
    !> CGGSVD 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 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 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 REAL array, dimension (N)
    !>

    BETA

    !>          BETA is REAL 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 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 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 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 array, dimension (max(3*N,M,P)+N)
    !>

    RWORK

    !>          RWORK is REAL 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 CTGSJA.
    !>

Internal Parameters:

    !>  TOLA    REAL
    !>  TOLB    REAL
    !>          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)*MACHEPS,
    !>                   TOLB = MAX(P,N)*norm(B)*MACHEPS.
    !>          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 335 of file cggsvd.f.

Author

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