计算满足给定阈值的部分奇异值分解的混合算法

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-08-06 DOI:10.1007/s11075-024-01906-9

James Baglama, Jonathan A. Chávez-Casillas, Vasilije Perović

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引用次数: 0

摘要

在本文中，我们描述了一种用于计算超过给定阈值的所有奇异三元组的新型混合算法，并提供了该算法在 MATLAB/Octave 和 R 中的实现。我们通过几个应用于矩阵补全和图像压缩的数值示例，说明了我们的代码的高性能及其在独立或更大数值方案中的易用性。我们提供了文档齐全的 MATLAB 和 R 代码供公众使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

A hybrid algorithm for computing a partial singular value decomposition satisfying a given threshold

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A hybrid algorithm for computing a partial singular value decomposition satisfying a given threshold

In this paper, we describe a new hybrid algorithm for computing all singular triplets above a given threshold and provide its implementation in MATLAB/Octave and R. The high performance of our codes and ease at which they can be used, either independently or within a larger numerical scheme, are illustrated through several numerical examples with applications to matrix completion and image compression. Well-documented MATLAB and R codes are provided for public use.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.