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Eigen::LeastSquareDiagonalPreconditioner

template<typename _Scalar>
class Eigen::LeastSquareDiagonalPreconditioner< _Scalar >

Jacobi preconditioner for LeastSquaresConjugateGradient.

This class allows to approximately solve for A' A x = A' b problems assuming A' A is a diagonal matrix. In other words, this preconditioner neglects all off diagonal entries and, in Eigen's language, solves for:

(A.adjoint() * A).diagonal().asDiagonal() * x = b
Template Parameters
_Scalar the type of the scalar.

This class follows the sparse solver concept .

The diagonal entries are pre-inverted and stored into a dense vector.

See also
class LeastSquaresConjugateGradient, class DiagonalPreconditioner

The documentation for this class was generated from the following file: