PCL
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Singular value decomposition algorithm for Matrix and Vector objects. More...
#include <Algebra.h>
Public Types | |
using | algorithm_implementation = GenericSVD< double > |
using | matrix = algorithm_implementation::matrix |
using | matrix_element = matrix::element |
using | vector = algorithm_implementation::vector |
using | vector_component = vector::component |
Public Types inherited from pcl::GenericSVD< double > | |
using | algorithm_implementation = GenericInPlaceSVD< double > |
using | matrix = typename algorithm_implementation::matrix |
using | matrix_element = typename matrix::element |
using | vector = typename algorithm_implementation::vector |
using | vector_component = typename vector::component |
Public Member Functions | |
SVD (const matrix &A) | |
Public Member Functions inherited from pcl::GenericSVD< double > | |
GenericSVD (const matrix &A) | |
int | IndexOfLargestSingularValue () const |
int | IndexOfSmallestSingularValue () const |
Additional Inherited Members | |
Public Attributes inherited from pcl::GenericSVD< double > | |
matrix | U |
matrix | V |
vector | W |
SVD is a template instantiation of GenericSVD for the double type. SVD works with Matrix and Vector objects. Matrix and Vector are template instantiations of GenericMatrix and GenericVector, respectively, for the double type.
using pcl::SVD::algorithm_implementation = GenericSVD<double> |
using pcl::SVD::matrix_element = matrix::element |
using pcl::SVD::vector_component = vector::component |
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inline |
Singular Value Decomposition: A = U*W*Vt
The dimensions of A are n rows and m columns. U is an n x m matrix. The m components of W are the positive diagonal elements of W, and each column of V (m x m) is the eigenvector for the corresponding element of W.
On output, this constructor stores U, W and V in the corresponding members of this object.