cgelss - compute the minimum norm solution to a complex linear least squares problem
SUBROUTINE CGELSS( M, N, NRHS, A, LDA, B, LDB, SING, RCOND, IRANK, * WORK, LDWORK, WORK2, INFO) COMPLEX A(LDA,*), B(LDB,*), WORK(*) INTEGER M, N, NRHS, LDA, LDB, IRANK, LDWORK, INFO REAL RCOND REAL SING(*), WORK2(*)
SUBROUTINE CGELSS_64( M, N, NRHS, A, LDA, B, LDB, SING, RCOND, * IRANK, WORK, LDWORK, WORK2, INFO) COMPLEX A(LDA,*), B(LDB,*), WORK(*) INTEGER*8 M, N, NRHS, LDA, LDB, IRANK, LDWORK, INFO REAL RCOND REAL SING(*), WORK2(*)
SUBROUTINE GELSS( [M], [N], [NRHS], A, [LDA], B, [LDB], SING, RCOND, * IRANK, [WORK], [LDWORK], [WORK2], [INFO]) COMPLEX, DIMENSION(:) :: WORK COMPLEX, DIMENSION(:,:) :: A, B INTEGER :: M, N, NRHS, LDA, LDB, IRANK, LDWORK, INFO REAL :: RCOND REAL, DIMENSION(:) :: SING, WORK2
SUBROUTINE GELSS_64( [M], [N], [NRHS], A, [LDA], B, [LDB], SING, * RCOND, IRANK, [WORK], [LDWORK], [WORK2], [INFO]) COMPLEX, DIMENSION(:) :: WORK COMPLEX, DIMENSION(:,:) :: A, B INTEGER(8) :: M, N, NRHS, LDA, LDB, IRANK, LDWORK, INFO REAL :: RCOND REAL, DIMENSION(:) :: SING, WORK2
#include <sunperf.h>
void cgelss(int m, int n, int nrhs, complex *a, int lda, complex *b, int ldb, float *sing, float rcond, int *irank, int *info);
void cgelss_64(long m, long n, long nrhs, complex *a, long lda, complex *b, long ldb, float *sing, float rcond, long *irank, long *info);
cgelss computes the minimum norm solution to a complex linear least squares problem:
Minimize 2-norm(| b - A*x |).
using the singular value decomposition (SVD) of A. A is an M-by-N matrix which may be rank-deficient.
Several right hand side vectors b and solution vectors x can be handled in a single call; they are stored as the columns of the M-by-NRHS right hand side matrix B and the N-by-NRHS solution matrix X.
The effective rank of A is determined by treating as zero those singular values which are less than RCOND times the largest singular value.
min(m,n)
rows of A are overwritten with
its right singular vectors, stored rowwise.
SING(i)
< = RCOND*SING(1) are treated as zero.
If RCOND < 0, machine precision is used instead.
WORK(1)
returns the optimal LDWORK.
max(M,N,NRHS)
For good performance, LDWORK should generally be larger.
If LDWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of the WORK array, returns this value as the first entry of the WORK array, and no error message related to LDWORK is issued by XERBLA.
dimension(5*min(M,N))
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: the algorithm for computing the SVD failed to converge; if INFO = i, i off-diagonal elements of an intermediate bidiagonal form did not converge to zero.