The task of extracting from a Krylov decomposition the approximation to an eigenpair that yields the smallest backward error can be phrased as finding the smallest perturbation which makes an associated matrix pair uncontrollable. Exploiting this relationship, we propose a new deflation criterion, which potentially admits earlier deflations than standard deflation criteria. Along these lines, a new deflation procedure for shift-and-invert Krylov methods is developed. Numerical experiments demonstrate the merits and limitations of this approach. © 2007 Università degli Studi di Ferrara
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...
Aggressive early deflation has proven to significantly enhance the convergence of the QR algorithm f...
Consider solving a sequence of linear systems A_{(i)}x^{(i)}=b^{(i)}, i=1, 2, ... where A₍ᵢ₎ ϵℂⁿᵡⁿ ...
Abstract. We consider deflation and augmentation techniques for accelerating the convergence of Kryl...
AbstractWe provide an overview of existing strategies which compensate for the deterioration of conv...
AbstractWe discuss a class of deflated block Krylov subspace methods for solving large scale matrix ...
Many problems in engineering, numerical simulations in physics etc. require the solution of long seq...
This thesis studies two classes of numerical linear algebra problems, approximating the product of a...
An overview of projection methods based on Krylov subspaces are given with emphasis on their applica...
In this addendum to an earlier paper by the author, it is shown how to compute a Krylov decompositi...
This paper starts o with studying simple extrapolation methods for the classical iteration schemes s...
This paper starts o with studying simple extrapolation methods for the classical iteration schemes ...
New variants of Krylov subspace methods for numerical solution of linear systems, eigenvalue, and mo...
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...
Aggressive early deflation has proven to significantly enhance the convergence of the QR algorithm f...
Consider solving a sequence of linear systems A_{(i)}x^{(i)}=b^{(i)}, i=1, 2, ... where A₍ᵢ₎ ϵℂⁿᵡⁿ ...
Abstract. We consider deflation and augmentation techniques for accelerating the convergence of Kryl...
AbstractWe provide an overview of existing strategies which compensate for the deterioration of conv...
AbstractWe discuss a class of deflated block Krylov subspace methods for solving large scale matrix ...
Many problems in engineering, numerical simulations in physics etc. require the solution of long seq...
This thesis studies two classes of numerical linear algebra problems, approximating the product of a...
An overview of projection methods based on Krylov subspaces are given with emphasis on their applica...
In this addendum to an earlier paper by the author, it is shown how to compute a Krylov decompositi...
This paper starts o with studying simple extrapolation methods for the classical iteration schemes s...
This paper starts o with studying simple extrapolation methods for the classical iteration schemes ...
New variants of Krylov subspace methods for numerical solution of linear systems, eigenvalue, and mo...
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...