Advanced Search

Query:

Fill in the form and click »Search«...

Format:

Display: entries per page entries

Zbl 0863.65016
Lehoucq, R.B.; Sorensen, D.C.
Deflation techniques for an implicitly restarted Arnoldi iteration. (English)
[J] SIAM J. Matrix Anal. Appl. 17, No.4, 789-821 (1996). ISSN 0895-4798; ISSN 1095-7162/e

A deflation procedure is introduced that is designed to improve the convergence of an implicitly restarted Arnoldi iteration for computing a few eigenvalues of a large matrix. A numerically stable scheme is introduced that implicitly deflates the converged approximations from the iteration.\par Two forms of implicit deflation are presented. One is locking operation, another is purging operation. Convergence of the iteration is improved and a reduction in computational effort is also achieved. The deflation strategies make it possible to compute multiple or clustered eigenvalues with a single vector restart method. A brief survey of and comparisons with other deflated processes are given and some numerical results are illustrated.
[Xie Shenquan (Xiangtan)]

MSC 2000:: *65F15 Eigenvalues (numerical linear algebra)

Keywords: Lanczos method; numerical stability; deflation; convergence; restarted Arnoldi iteration; eigenvalues; large matrix; comparisons; numerical results

Comment on this Item PDF MathML XML ASCII DVI PS BibTeX Online Ordering Article Journal

	Scientific prize winners of the ICM 2010
	Overhang
	Lie groups, physics and geometry. An introduction for physicists, engineers and chemists.

Advanced Search

Zentralblatt MATH Berlin [Germany]