A Jacobi-Davidson type SVD method

被引：49
|
作者：
Hochstenbach, ME [1 ]
机构：
[1] Univ Utrecht, Inst Math, NL-3508 TA Utrecht, Netherlands
来源：
SIAM JOURNAL ON SCIENTIFIC COMPUTING | 2001年 / 23卷 / 02期
关键词：
Jacobi-Davidson; singular value decomposition ( SVD); singular values; singular vectors; norm; augmented matrix; correction equation; (inexact) accelerated Newton; improving singular values;
D O I：
10.1137/S1064827500372973
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We discuss a new method for the iterative computation of a portion of the singular values and vectors of a large sparse matrix. Similar to the Jacobi Davidson method for the eigenvalue problem, we compute in each step a correction by (approximately) solving a correction equation. We give a few variants of this Jacobi Davidson SVD (JDSVD) method with their theoretical properties. It is shown that the JDSVD can be seen as an accelerated (inexact) Newton scheme. We experimentally compare the method with some other iterative SVD methods.
引用
收藏
页码：606 / 628
页数：23
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