GELSS: 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.
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GELSS: 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.
◆ la_cgelss()
| la_lapack::gelss::la_cgelss |
◆ la_dgelss()
| la_lapack::gelss::la_dgelss |
◆ la_qgelss()
| la_lapack::gelss::la_qgelss |
◆ la_sgelss()
| la_lapack::gelss::la_sgelss |
◆ la_wgelss()
| la_lapack::gelss::la_wgelss |
◆ la_zgelss()
| la_lapack::gelss::la_zgelss |
The documentation for this interface was generated from the following file:
1.13.2