#include <nnls.h>
Public Types | |
typedef M | matrix_type |
typedef V | vector_type |
typedef matrix_type::value_type | value_type |
typedef matrix_type::size_type | size_type |
Public Member Functions | |
nnls (const matrix_type &matrix, const vector_type &vector) | |
An object constructor. | |
template<class sV , class sM > | |
void | solve (sV &ret, sM &cov) const |
Solving operaton. | |
template<class sV > | |
void | solve (sV &ret) const |
The Non-Negative Least Squares problem is very simular to the Least Squares Problem and has many applications in physics. The NNLS consists of finding vector such that euclidean norm is minimal but . Where matrix and vector are given. It is trivial that for these two problems may be the same but not always.
lsp::nnls< M, V >::nnls | ( | const matrix_type & | matrix, | |
const vector_type & | vector | |||
) | [inline] |
An object constructor.
[in,out] | matrix | The given matrix |
[in,out] | vector | The given vector |
void lsp::nnls< M, V >::solve | ( | sV & | ret, | |
sM & | cov | |||
) | const [inline] |
Solving operaton.
[out] | ret | Desired vector |
[out] | cov | The covariation matrix of the |
References lsp::is_vector_elem(), and lsp::swap_indexes().