AbstractThe QR algorithm is one of the most widely used algorithms for calculating the eigenvalues of matrices. The multishift QR algorithm with multiplicity m is a version that effects m iterations of the QR algorithm at a time. It is known that roundoff errors cause the multishift QR algorithm to perform poorly when m is large. In this paper the mechanism by which the shifts are transmitted through the matrix in the course of a multishift QR iteration is identified. Numerical evidence showing that the mechanism works well when m is small and poorly when m is large is presented. When the mechanism works poorly, the convergence of the algorithm is degraded proportionately
Rapid convergence of the shifted QR algorithm on symmetric matrices was shown more than fifty years ...
Aggressive early deflation has proven to significantly enhance the convergence of the QR algorithm f...
The QR algorithm is the method of choice for computing all eigenvalues of a dense nonsymmetric matri...
ABSTRACT – The multi-shift QR algorithm for approximating the eigenvalues of a full matrix is known ...
The role of larger bulges in the QR algorithm is controversial. Large bulges are infamous for having...
AbstractI reconsider some hypotheses concerning errant behaviors of the m-tuple QP iteration for rea...
Each iteration of the multishift QR algorithm of Bai and Demmel requires the computation of a "...
We present a new deflation criterion for the multishift QR algorithm motivated by convergence analys...
matrix computations, eigenvalues, QR algorithm Each iteration of the multishift QR algorithm of Bai ...
This paper presents two modifications to the multi-shift QR algorithm that significantly increase it...
Recently a generalization of Francis’s implicitly shifted QR-algorithm was proposed, notably widenin...
The implicitly shifted (bulge chasing ) QZ algorithm is the most popular method for solving the gene...
在計算矩陣的特徵值(eigenvalues)中,QR演算法是一種常見的技巧. 尤其如果使用適當的移位,將可以較快得到特徵值. 在本文中提出一種新的移位策略, 我們證明這各方法是可行的,而且可適用於任何...
AbstractIn 1989, Bai and Demmel proposed the multishift QR algorithm for eigenvalue problems. Althou...
We develop a framework for proving rapid convergence of shifted QR algorithms which use Ritz values ...
Rapid convergence of the shifted QR algorithm on symmetric matrices was shown more than fifty years ...
Aggressive early deflation has proven to significantly enhance the convergence of the QR algorithm f...
The QR algorithm is the method of choice for computing all eigenvalues of a dense nonsymmetric matri...
ABSTRACT – The multi-shift QR algorithm for approximating the eigenvalues of a full matrix is known ...
The role of larger bulges in the QR algorithm is controversial. Large bulges are infamous for having...
AbstractI reconsider some hypotheses concerning errant behaviors of the m-tuple QP iteration for rea...
Each iteration of the multishift QR algorithm of Bai and Demmel requires the computation of a "...
We present a new deflation criterion for the multishift QR algorithm motivated by convergence analys...
matrix computations, eigenvalues, QR algorithm Each iteration of the multishift QR algorithm of Bai ...
This paper presents two modifications to the multi-shift QR algorithm that significantly increase it...
Recently a generalization of Francis’s implicitly shifted QR-algorithm was proposed, notably widenin...
The implicitly shifted (bulge chasing ) QZ algorithm is the most popular method for solving the gene...
在計算矩陣的特徵值(eigenvalues)中,QR演算法是一種常見的技巧. 尤其如果使用適當的移位,將可以較快得到特徵值. 在本文中提出一種新的移位策略, 我們證明這各方法是可行的,而且可適用於任何...
AbstractIn 1989, Bai and Demmel proposed the multishift QR algorithm for eigenvalue problems. Althou...
We develop a framework for proving rapid convergence of shifted QR algorithms which use Ritz values ...
Rapid convergence of the shifted QR algorithm on symmetric matrices was shown more than fifty years ...
Aggressive early deflation has proven to significantly enhance the convergence of the QR algorithm f...
The QR algorithm is the method of choice for computing all eigenvalues of a dense nonsymmetric matri...