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Add a CG-based solver for rectangular least-square problems (bug #975).
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@@ -12,24 +12,26 @@
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* This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse.
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* Those solvers are accessible via the following classes:
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* - ConjugateGradient for selfadjoint (hermitian) matrices,
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* - LSCG for rectangular least-square problems,
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* - BiCGSTAB for general square matrices.
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*
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* These iterative solvers are associated with some preconditioners:
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* - IdentityPreconditioner - not really useful
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* - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices.
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* - IncompleteILUT - incomplete LU factorization with dual thresholding
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* - IncompleteLUT - incomplete LU factorization with dual thresholding
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*
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* Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport.
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*
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* \code
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* #include <Eigen/IterativeLinearSolvers>
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* \endcode
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\code
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#include <Eigen/IterativeLinearSolvers>
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\endcode
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*/
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#include "src/IterativeLinearSolvers/SolveWithGuess.h"
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#include "src/IterativeLinearSolvers/IterativeSolverBase.h"
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#include "src/IterativeLinearSolvers/BasicPreconditioners.h"
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#include "src/IterativeLinearSolvers/ConjugateGradient.h"
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#include "src/IterativeLinearSolvers/LeastSquareConjugateGradient.h"
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#include "src/IterativeLinearSolvers/BiCGSTAB.h"
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#include "src/IterativeLinearSolvers/IncompleteLUT.h"
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