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解大规模非对称矩阵特征问题的精化Arnoldi方法的一种变形 被引量:8

A VARIANT OF THE REFINED ARNOLDI METHOD FOR LARGE SCALE MATRIX EIGENPROBLEMS
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摘要 The refined Arnoldi method proposed by Jia is used for computing some eigen-pairs of large matrices. In contrast to the Arnoldi method, the fundamental dif-ference is that the refined method seeks certain refined Ritz vectors, which aredifferent from the Ritz vectors obtained by the Arnoldi method, from a projection space with minimal residuals to approximate the desired eigenvectors. In com-parison with the Ritz vectors, the refined Ritz vectors are guaranteed to converge theoretically and can converge much faster numerically. In this paper we propose to replace the Ritz values, obtained by the Arnoldi method with respect to a Krylovsubspace, by the ones obtained with respect to the subspace spanned by the refined Ritz vectors. We discuss how to compute these new approximations cheaply and reliably. Theoretical error bounds between the original Ritz values and the new Ritz values are established. Finally, we present a variant of the refined Arnoldi al-gorithm for an augmented Krylov subspace and discuss restarting issue. Numerical results confirm efficiency of the new algorithm. The refined Arnoldi method proposed by Jia is used for computing some eigen-pairs of large matrices. In contrast to the Arnoldi method, the fundamental difference is that the refined method seeks certain refined Ritz vectors, which are different from the Ritz vectors obtained by the Arnoldi method, from a projection space with minimal residuals to approximate the desired eigenvectors. In comparison with the Ritz vectors, the refined Ritz vectors are guaranteed to converge theoretically and can converge much faster numerically. In this paper we propose to replace the Ritz values, obtained by the Arnoldi method with respect to a Krylov subspace, by the ones obtained with respect to the subspace spanned by the refined Ritz vectors. We discuss how to compute these new approximations cheaply and reliably. Theoretical error bounds between the original Ritz values and the new Ritz values are established. Finally, we present a variant of the refined Arnoldi algorithm for an augmented Krylov subspace and discuss restarting issue. Numerical results confirm efficiency of the new algorithm.
出处 《数值计算与计算机应用》 CSCD 北大核心 2003年第2期101-110,共10页 Journal on Numerical Methods and Computer Applications
基金 国家重点基础研究发展规划项目(973)(G1999032805) 高等学校骨干教师基金资助
关键词 大规模非对称矩阵 特征问题 精化Arnoldi方法 Ritz向量 RITZ值 精化投影方法 近似特征值 Ritz pairs, Refined Ritz pairs, the Arnoldi process, the Refined Arnoldi method, Rayleigh quotient, Approximate eigenvalue
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参考文献18

  • 1Z. Bai, J. Demmel, J. Dongarra, A. Ruhe and H. A. van der Vorst, Templates for the Solution of Algebraic Eigenvalue Problems: A Practical Guide, SIAM, Philadelpha, PA, 2000.
  • 2E. R. Davidson, The iterative calculation of a few of the lowest eigenvalues and corresponding eigenvectors of large real symmetric matrices, J. Comput. Phys., 17 (1975), 87-94.
  • 3Z. Jia, The convergence of generalized Lanczos methods for large unsymmetric eigenproblems,SIAM J. Matrix Anal. Appl., 16 (1995), 843-862.
  • 4Z. Jia, Refined iterative algorithms based on Arnoldi's process for large unsymmetric eigenproblem, Linear Algebra Appl., 259 (1997), 1-23.
  • 5Z. Jia, Generalized block Lanczos methods for large unsymmetric eigenproblems, Numer. Math.,80 (1998), 239-266.
  • 6Z. Jia, A refined iterative algorithm based on the block Arnoldi process for large unsymmetric eigenproblems, Linear Algebra Appl., 270 (1998), 171-189.
  • 7Z. Jia, Polynomial characterizations of the approximate eigenvectors by the refined Arnoldi method and an implicitly restarted refined Arnoldi algorithm, Linear Algebra Appl., 287 (1999),191-214.
  • 8Z. Jia, Composite orthogonal projection methods for large eigenproblems, Science in China (SeriesA), 42 (1999), 577-585.
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