There is one prototype of gelss
available, please see below.
gelss( MatrixA& a, MatrixB& b, VectorS& s, const Scalar >, int_t& rank );
gelss (short for $FRIENDLY_NAME)
provides a C++ interface to LAPACK routines SGELSS, DGELSS, CGELSS, and
ZGELSS. 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.
The selection of the LAPACK routine is done during compile-time, and
is determined by the type of values contained in type MatrixA.
The type of values is obtained through the value_type
meta-function typename value_type<MatrixA>::type. The dispatching table below illustrates
to which specific routine the code path will be generated.
Table 1.183. Dispatching of gelss
|
Value type of MatrixA |
LAPACK routine |
|---|---|
|
|
SGELSS |
|
|
DGELSS |
|
|
CGELSS |
|
|
ZGELSS |
Defined in header boost/numeric/bindings/lapack/driver/gelss.hpp.
Parameters
The definition of term 1
The definition of term 2
The definition of term 3.
Definitions may contain paragraphs.
#include <boost/numeric/bindings/lapack/driver/gelss.hpp> using namespace boost::numeric::bindings; lapack::gelss( x, y, z );
this will output
[5] 0 1 2 3 4 5