The theory of the convergence of Krylov subspace iterations for linear systems of equations (conjugate gradients, biconjugate gradients, GMRES, QMR, Bi-CGSTAB, ...) is reviewed. For a computation of this kind, an estimated asymptotic convergence factor rho less than 1 can be derived by solving a problem of potential theory or conformal mapping. Six approximations are involved in reducing the actual computation to this scalar estimate. These six approximations are discussed in a systematic way and illustrated by a sequence of examples computed with tools of numerical conformal mapping and semidefinite programming
In this chapter we will present an overview of a number of related iterative methods for the solutio...
Abstract. Krylov subspace methods are strongly related to polynomial spaces and their convergence an...
Consider solving a sequence of linear systems A_{(i)}x^{(i)}=b^{(i)}, i=1, 2, ... where A₍ᵢ₎ ϵℂⁿᵡⁿ ...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
This diploma thesis from 2006 reviews various definitions of matrix functions and polynomial Krylov ...
There is a class of linear problems for which the computation of the matrix-vector product is very ...
Abstract. There is a class of linear problems for which the computation of the matrix-vector product...
In most practical cases, the convergence of the GMRES method applied to a linear algebraic system Ax...
Title: Analysis of Krylov subspace methods Author: Tomáš Gergelits Department: Department of Numeric...
We present a general analytical model which describes the superlinear convergence of Krylov subspace...
AbstractIn the present paper, we give some convergence results of the global minimal residual method...
Title: Krylov subspace methods: Theory, applications and interconnections Author: Tomáš Gergelits De...
When solving PDE's by means of numerical methods one often has to deal with large systems of linear ...
In this paper we analyze the convergence of some commonly used Krylov subspace methods for computing...
AbstractKrylov subspace methods have been recently considered to solve singular linear systems Ax=b....
In this chapter we will present an overview of a number of related iterative methods for the solutio...
Abstract. Krylov subspace methods are strongly related to polynomial spaces and their convergence an...
Consider solving a sequence of linear systems A_{(i)}x^{(i)}=b^{(i)}, i=1, 2, ... where A₍ᵢ₎ ϵℂⁿᵡⁿ ...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
This diploma thesis from 2006 reviews various definitions of matrix functions and polynomial Krylov ...
There is a class of linear problems for which the computation of the matrix-vector product is very ...
Abstract. There is a class of linear problems for which the computation of the matrix-vector product...
In most practical cases, the convergence of the GMRES method applied to a linear algebraic system Ax...
Title: Analysis of Krylov subspace methods Author: Tomáš Gergelits Department: Department of Numeric...
We present a general analytical model which describes the superlinear convergence of Krylov subspace...
AbstractIn the present paper, we give some convergence results of the global minimal residual method...
Title: Krylov subspace methods: Theory, applications and interconnections Author: Tomáš Gergelits De...
When solving PDE's by means of numerical methods one often has to deal with large systems of linear ...
In this paper we analyze the convergence of some commonly used Krylov subspace methods for computing...
AbstractKrylov subspace methods have been recently considered to solve singular linear systems Ax=b....
In this chapter we will present an overview of a number of related iterative methods for the solutio...
Abstract. Krylov subspace methods are strongly related to polynomial spaces and their convergence an...
Consider solving a sequence of linear systems A_{(i)}x^{(i)}=b^{(i)}, i=1, 2, ... where A₍ᵢ₎ ϵℂⁿᵡⁿ ...