. . "On the Moore-Penrose inverse in solving saddle-point systems with singular diagonal blocks"@en . . . "Kozubek, Tom\u00E1\u0161" . . "[56FE65208C87]" . . "US - Spojen\u00E9 st\u00E1ty americk\u00E9" . . . "156429" . "15310" . . "4" . . "On the Moore-Penrose inverse in solving saddle-point systems with singular diagonal blocks"@en . . "1070-5325" . "This paper deals with the role of the generalized inverses in solving saddle-point systems arising naturally in the solution of many scientific and engineering problems when finite-element tearing and interconnecting based domain decomposition methods are used to the numerical solution. It was shown that the Moore-Penrose inverse may be obtained in this case at negligible cost by projecting an arbitrary generalized inverse using orthogonal projectors. Applying an eigenvalue analysis based on the Moore-Penrose inverse, we proved that for simple model problems, the number of conjugate gradient iterations required for the solution of associate dual systems does not depend on discretization norms. The theoretical results were confirmed by numerical experiments with linear elasticity problems." . "On the Moore-Penrose inverse in solving saddle-point systems with singular diagonal blocks" . "23"^^ . . "P(GA101/08/0574), S, Z(MSM6198910027)" . "Markopoulos, Alexandros" . "10.1002/nla.798" . "Ku\u010Dera, Radek" . . . "Machalov\u00E1, Jitka" . . "4"^^ . . "RIV/61989592:15310/12:33141645!RIV13-MSM-15310___" . "On the Moore-Penrose inverse in solving saddle-point systems with singular diagonal blocks" . . "19" . . . "Numerical Linear Algebra with Applications" . "condition number; domain decomposition methods; saddle-point systems; orthogonal projectors; Moore-Penrose inverse"@en . "RIV/61989592:15310/12:33141645" . "1"^^ . . "000306278800005" . . "This paper deals with the role of the generalized inverses in solving saddle-point systems arising naturally in the solution of many scientific and engineering problems when finite-element tearing and interconnecting based domain decomposition methods are used to the numerical solution. It was shown that the Moore-Penrose inverse may be obtained in this case at negligible cost by projecting an arbitrary generalized inverse using orthogonal projectors. Applying an eigenvalue analysis based on the Moore-Penrose inverse, we proved that for simple model problems, the number of conjugate gradient iterations required for the solution of associate dual systems does not depend on discretization norms. The theoretical results were confirmed by numerical experiments with linear elasticity problems."@en .