Robust Approximate Inverse Preconditioning for the Conjugate Gradient Method
作者： Michele Benzi , Jane K. Cullum , Miroslav Tuma
DOI: 10.1137/S1064827599356900
关键词: Sparse matrix 、 Preconditioner 、 Derivation of the conjugate gradient method 、 Mathematics 、 Symmetric matrix 、 Matrix (mathematics) 、 Conjugate gradient method 、 Applied mathematics 、 Gradient method 、 Algebra 、 Conjugate residual method 、 Computational mathematics
摘要: We present a variant of the AINV factorized sparse approximate inverse algorithm which is applicable to any symmetric positive definite matrix. The new preconditioner breakdown-free and, when used in conjunction with conjugate gradient method, results reliable solver for highly ill-conditioned linear systems. also investigate an alternative approach stable algorithm, based on idea diagonally compensated reduction matrix entries. numerical tests challenging systems arising from finite element modeling elasticity and diffusion problems are presented.
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