Fast dual-MGS block-factorization algorithm for dense MoM matrices

被引：33

作者：

Burkholder, RJ ^{[1
]}

Lee, JF ^{[1
]}

机构：

[1] Ohio State Univ, Dept Elect Engn, Electrosci Lab, Columbus, OH 43212 USA

来源：

IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION | 2004年 / 52卷 / 07期

关键词：

singular value decomposition (SVD); fast solvers; integral equations; method of moments (MoM); matrix decomposition; iterative methods;

D O I：

10.1109/TAP.2004.831333

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A robust method is introduced for efficiently compressing dense method of moments (MoM) matrices using a dual modified Gram-Schmidt block-QR-factorization algorithm based on low-rank singular value decomposition. The compression is achieved without generating the full matrix or even full subblocks of the matrix. The compressed matrix may then be used in the iterative solution of the MoM problem. The method is very robust because it uses a reduced set of the original matrix entries to perform the compression. Furthermore, it does not depend on the analytic form of the Green's function, so it may be applied to arbitrarily complex media.

引用

页码：1693 / 1699

页数：7

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