AbstractIt is shown that the four vector extrapolation methods, minimal polynomial extrapolation, reduced rank extrapolation, modified minimal polynomial extrapolation, and topological epsilon algorithm, when applied to linearly generated vector sequences, are Krylov subspace methods, and are equivalent to some well known conjugate gradient type methods. A unified recursive method that includes the conjugate gradient, conjugate residual, and generalized conjugate gradient methods is developed. Finally, the error analyses for these methods are unified, and some known and some new error bounds for them are given
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
Many scientific applications require to solve successively linear systems Ax=b with different right-...
Abstract. Recent results on residual smoothing are reviewed, and it is observed that certain of thes...
AbstractIt is shown that the four vector extrapolation methods, minimal polynomial extrapolation, re...
NoThe four vector extrapolation methods, minimal polynomial extrapolation, reduced rank extrapolatio...
AbstractThe present paper is a survey of the most popular vector extrapolation methods such as the r...
Extrapolation methods can be used to accelerate the convergence of vector sequences. It is shown ho...
AbstractAn important problem that arises in different areas of science and engineering is that of co...
AbstractIn two previous papers [10,11] convergence and stability results for the following vector ex...
AbstractThe minimal polynomial extrapolation (MPE) and reduced rank extrapolation (RRE) are two very...
AbstractThe recursive projection algorithm derived in a previous paper is related to several well-kn...
In this thesis, we study polynomial extrapolation methods. We discuss the design and implementation ...
Nous nous intéressons, dans cette thèse, à l'étude des méthodes d'extrapolation polynômiales et à l'...
In this chapter we will present an overview of a number of related iterative methods for the solutio...
Abstract. We present a deflated version of the conjugate gradient algorithm for solving linear syste...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
Many scientific applications require to solve successively linear systems Ax=b with different right-...
Abstract. Recent results on residual smoothing are reviewed, and it is observed that certain of thes...
AbstractIt is shown that the four vector extrapolation methods, minimal polynomial extrapolation, re...
NoThe four vector extrapolation methods, minimal polynomial extrapolation, reduced rank extrapolatio...
AbstractThe present paper is a survey of the most popular vector extrapolation methods such as the r...
Extrapolation methods can be used to accelerate the convergence of vector sequences. It is shown ho...
AbstractAn important problem that arises in different areas of science and engineering is that of co...
AbstractIn two previous papers [10,11] convergence and stability results for the following vector ex...
AbstractThe minimal polynomial extrapolation (MPE) and reduced rank extrapolation (RRE) are two very...
AbstractThe recursive projection algorithm derived in a previous paper is related to several well-kn...
In this thesis, we study polynomial extrapolation methods. We discuss the design and implementation ...
Nous nous intéressons, dans cette thèse, à l'étude des méthodes d'extrapolation polynômiales et à l'...
In this chapter we will present an overview of a number of related iterative methods for the solutio...
Abstract. We present a deflated version of the conjugate gradient algorithm for solving linear syste...
AbstractThe approximate solutions in standard iteration methods for linear systems Ax=b, with A an n...
Many scientific applications require to solve successively linear systems Ax=b with different right-...
Abstract. Recent results on residual smoothing are reviewed, and it is observed that certain of thes...