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Eigen  3.4.0
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Detailed Description

This module provides SVD decomposition for matrices (both real and complex). Two decomposition algorithms are provided:

  • JacobiSVD implementing two-sided Jacobi iterations is numerically very accurate, fast for small matrices, but very slow for larger ones.
  • BDCSVD implementing a recursive divide & conquer strategy on top of an upper-bidiagonalization which remains fast for large problems. These decompositions are accessible via the respective classes and following MatrixBase methods:
  • MatrixBase::jacobiSvd()
  • MatrixBase::bdcSvd()
#include <Eigen/SVD>

Classes

class  Eigen::BDCSVD< _MatrixType >
 class Bidiagonal Divide and Conquer SVD More...
class  Eigen::JacobiSVD< _MatrixType, QRPreconditioner >
 Two-sided Jacobi SVD decomposition of a rectangular matrix. More...
class  Eigen::SVDBase< Derived >
 Base class of SVD algorithms. More...