In many applications it appears that the initial convergence of preconditioned Krylov solvers is slow. The reason for this is that a number of small eigenvalues are present. After these bad eigenvector components are approximated, the fast superlinear convergence sets in. A way to have fast convergence from the start is to remove these components by a projection. In this paper we give a comparison of some of these projection operators.
Many problems in scientific computation require to solve linear systems. Recent efficient solvers ar...
Many problems in scientific computation require to solve linear systems. Recent efficient solvers ar...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
In this paper we present some aspects of recent works we have been developping on preconditioning te...
Consider solving a sequence of linear systems A_{(i)}x^{(i)}=b^{(i)}, i=1, 2, ... where A₍ᵢ₎ ϵℂⁿᵡⁿ ...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
summary:In recent papers Ruhe suggested a rational Krylov method for nonlinear eigenproblems knittin...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
In recent papers Ruhe [10], [12] suggested a rational Krylov method for nonlinear eigenproblems knit...
In recent papers Ruhe [10], [12] suggested a rational Krylov method for nonlinear eigenproblems knit...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
The theory of the convergence of Krylov subspace iterations for linear systems of equations (conjuga...
Many problems in scientific computation require to solve linear systems. Recent efficient solvers ar...
Many problems in scientific computation require to solve linear systems. Recent efficient solvers ar...
Many problems in scientific computation require to solve linear systems. Recent efficient solvers ar...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
In this paper we present some aspects of recent works we have been developping on preconditioning te...
Consider solving a sequence of linear systems A_{(i)}x^{(i)}=b^{(i)}, i=1, 2, ... where A₍ᵢ₎ ϵℂⁿᵡⁿ ...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
summary:In recent papers Ruhe suggested a rational Krylov method for nonlinear eigenproblems knittin...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
In recent papers Ruhe [10], [12] suggested a rational Krylov method for nonlinear eigenproblems knit...
In recent papers Ruhe [10], [12] suggested a rational Krylov method for nonlinear eigenproblems knit...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
In these lecture notes an introduction to Krylov subspace solvers and preconditioners is presented. ...
The theory of the convergence of Krylov subspace iterations for linear systems of equations (conjuga...
Many problems in scientific computation require to solve linear systems. Recent efficient solvers ar...
Many problems in scientific computation require to solve linear systems. Recent efficient solvers ar...
Many problems in scientific computation require to solve linear systems. Recent efficient solvers ar...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...