stgsja (l) - Linux Manuals

stgsja: computes the generalized singular value decomposition (GSVD) of two real upper triangular (or trapezoidal) matrices A and B

NAME

STGSJA - computes the generalized singular value decomposition (GSVD) of two real upper triangular (or trapezoidal) matrices A and B

SYNOPSIS

SUBROUTINE STGSJA(

JOBU, JOBV, JOBQ, M, P, N, K, L, A, LDA, B, LDB, TOLA, TOLB, ALPHA, BETA, U, LDU, V, LDV, Q, LDQ, WORK, NCYCLE, INFO )

    

CHARACTER JOBQ, JOBU, JOBV

    

INTEGER INFO, K, L, LDA, LDB, LDQ, LDU, LDV, M, N, NCYCLE, P

    

REAL TOLA, TOLB

    

REAL A( LDA, * ), ALPHA( * ), B( LDB, * ), BETA( * ), Q( LDQ, * ), U( LDU, * ), V( LDV, * ), WORK( * )

PURPOSE

STGSJA computes the generalized singular value decomposition (GSVD) of two real upper triangular (or trapezoidal) matrices A and B. On entry, it is assumed that matrices A and B have the following forms, which may be obtained by the preprocessing subroutine SGGSVP from a general M-by-N matrix A and P-by-N matrix B:

       N-K-L  K    L

A =    K ( 0    A12  A13 ) if M-K-L >= 0;

    L ( 0     0   A23 )

M-K-L ( 0     0    0  )

     N-K-L  K    L

A =  K ( 0    A12  A13 ) if M-K-L < 0;

M-K ( 0     0   A23 )

     N-K-L  K    L

B =  L ( 0     0   B13 )

P-L ( 0     0    0  )
where the K-by-K matrix A12 and L-by-L matrix B13 are nonsingular upper triangular; A23 is L-by-L upper triangular if M-K-L >= 0, otherwise A23 is (M-K)-by-L upper trapezoidal.
On exit,

      Uaq*A*Q = D1*( 0 R ),    Vaq*B*Q = D2*( 0 R ),
where U, V and Q are orthogonal matrices, Zaq denotes the transpose of Z, R is a nonsingular upper triangular matrix, and D1 and D2 are ``diagonalaqaq matrices, which are of the following structures: 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 ) K

      L (  0    0   R22 ) L
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

    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.
R = ( 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 computation of the orthogonal transformation matrices U, V or Q is optional. These matrices may either be formed explicitly, or they may be postmultiplied into input matrices U1, V1, or Q1.

ARGUMENTS

JOBU (input) CHARACTER*1

= aqUaq: U must contain an orthogonal matrix U1 on entry, and the product U1*U is returned; = aqIaq: U is initialized to the unit matrix, and the orthogonal matrix U is returned; = aqNaq: U is not computed.

JOBV (input) CHARACTER*1

= aqVaq: V must contain an orthogonal matrix V1 on entry, and the product V1*V is returned; = aqIaq: V is initialized to the unit matrix, and the orthogonal matrix V is returned; = aqNaq: V is not computed.

JOBQ (input) CHARACTER*1

= aqQaq: Q must contain an orthogonal matrix Q1 on entry, and the product Q1*Q is returned; = aqIaq: Q is initialized to the unit matrix, and the orthogonal matrix Q is returned; = aqNaq: Q is not computed.

M (input) INTEGER

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

P (input) INTEGER

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

N (input) INTEGER

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

K (input) INTEGER

L (input) INTEGER K and L specify the subblocks in the input matrices A and B:
A23 = A(K+1:MIN(K+L,M),N-L+1:N) and B13 = B(1:L,N-L+1:N) of A and B, whose GSVD is going to be computed by STGSJA. See Further Details. A (input/output) REAL array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, A(N-K+1:N,1:MIN(K+L,M) ) contains the triangular matrix R or part of R. See Purpose for details.

LDA (input) INTEGER

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

B (input/output) REAL array, dimension (LDB,N)

On entry, the P-by-N matrix B. On exit, if necessary, B(M-K+1:L,N+M-K-L+1:N) contains a part of R. See Purpose for details.

LDB (input) INTEGER

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

TOLA (input) REAL

TOLB (input) REAL TOLA and TOLB are the convergence criteria for the Jacobi- Kogbetliantz iteration procedure. Generally, they are the same as used in the preprocessing step, say TOLA = max(M,N)*norm(A)*MACHEPS, TOLB = max(P,N)*norm(B)*MACHEPS.

ALPHA (output) REAL array, dimension (N)

BETA (output) 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) = diag(C),
BETA(K+1:K+L) = diag(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. Furthermore, if K+L < N, ALPHA(K+L+1:N) = 0 and
BETA(K+L+1:N) = 0.

U (input/output) REAL array, dimension (LDU,M)

On entry, if JOBU = aqUaq, U must contain a matrix U1 (usually the orthogonal matrix returned by SGGSVP). On exit, if JOBU = aqIaq, U contains the orthogonal matrix U; if JOBU = aqUaq, U contains the product U1*U. If JOBU = aqNaq, U is not referenced.

LDU (input) INTEGER

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

V (input/output) REAL array, dimension (LDV,P)

On entry, if JOBV = aqVaq, V must contain a matrix V1 (usually the orthogonal matrix returned by SGGSVP). On exit, if JOBV = aqIaq, V contains the orthogonal matrix V; if JOBV = aqVaq, V contains the product V1*V. If JOBV = aqNaq, V is not referenced.

LDV (input) INTEGER

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

Q (input/output) REAL array, dimension (LDQ,N)

On entry, if JOBQ = aqQaq, Q must contain a matrix Q1 (usually the orthogonal matrix returned by SGGSVP). On exit, if JOBQ = aqIaq, Q contains the orthogonal matrix Q; if JOBQ = aqQaq, Q contains the product Q1*Q. If JOBQ = aqNaq, Q is not referenced.

LDQ (input) INTEGER

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

WORK (workspace) REAL array, dimension (2*N)

NCYCLE (output) INTEGER

The number of cycles required for convergence.

INFO (output) INTEGER

= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
= 1: the procedure does not converge after MAXIT cycles.

PARAMETERS

MAXIT INTEGER

MAXIT specifies the total loops that the iterative procedure may take. If after MAXIT cycles, the routine fails to converge, we return INFO = 1. Further Details =============== STGSJA essentially uses a variant of Kogbetliantz algorithm to reduce min(L,M-K)-by-L triangular (or trapezoidal) matrix A23 and L-by-L matrix B13 to the form: U1aq*A13*Q1 = C1*R1; V1aq*B13*Q1 = S1*R1, where U1, V1 and Q1 are orthogonal matrix, and Zaq is the transpose of Z. C1 and S1 are diagonal matrices satisfying C1**2 + S1**2 = I, and R1 is an L-by-L nonsingular upper triangular matrix.