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NII Technical Report (NII-2007-009E)：GMRES Methods for Least Squares Problems
https://doi.org/10.20736/0000001238
https://doi.org/10.20736/00000012381ee236a5-f859-4e3c-ac48-8eef991c2cda
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
NII Technical Report (NII-2007-009E)：GMRES Methods for Least Squares Problems (757.0 kB)
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| Item type | レポート / Report(1) | |||||||||||||||
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| 公開日 | 2019-03-12 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | NII Technical Report (NII-2007-009E)：GMRES Methods for Least Squares Problems | |||||||||||||||
| 言語 | en | |||||||||||||||
| 言語 | ||||||||||||||||
| 言語 | eng | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | ja | |||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | テクニカルレポート | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | en | |||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | Technical Report | |||||||||||||||
| 資源タイプ | ||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||
| 資源タイプ | departmental bulletin paper | |||||||||||||||
| ID登録 | ||||||||||||||||
| ID登録 | 10.20736/0000001238 | |||||||||||||||
| ID登録タイプ | JaLC | |||||||||||||||
| 著者 |
速水, 謙
× 速水, 謙
× YIN, Jun-Feng
× 伊藤, 徳史
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| 抄録 | ||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||
| 内容記述 | The standard iterative method for solving large sparse least squares problems min_{x \in R^n} || b - A x ||_2, A \in R^{m x n} is the CGLS method, or its stabilized version LSQR, which applies the (preconditioned) conjugate gradient method to the normal equation A^T A x = A^T b. In this paper, we will consider alternative methods using a matrix B \in R^{n x m} and applying the Generalized Minimal Residual (GMRES) method to min_{z \in R^m} || b - A B z ||_2 or \min_{x \in R^n} || B b - B A x ||_2. Next, we give a sufficient condition concerning B for the GMRES methods to give a least squares solution without breakdown for arbitrary b, for over-determined, under-determined and possibly rank-deficient problems. We then give a convergence analysis of the GMRES methods as well as the CGLS method. Then, we propose using the robust incomplete factorization (RIF) for B. Finally, we show by numerical experiments on over-determined and under-determined problems that, for ill-conditioned problems, the GMRES methods with RIF give least squares solutions faster than the CGLS and LSQR methods with RIF. | |||||||||||||||
| 言語 | en | |||||||||||||||
| 書誌情報 |
ja : NIIテクニカル・レポート en : NII Technical Report p. 1-28, 発行日 2007-07-11 |
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| 出版者 | ||||||||||||||||
| 出版者 | 国立情報学研究所 | |||||||||||||||
| 言語 | ja | |||||||||||||||
| ISSN | ||||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||||
| 収録物識別子 | 1346-5597 | |||||||||||||||
