Explicit deflation in Golub-Kahan-Lanczos bidiagonalization methods

J. Baglama, V. Perović
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Abstract

. We discuss a simple, easily overlooked, explicit deflation procedure applied to Golub-Kahan-Lanczos Bidiagonalization (GKLB)-based methods to compute the next set of the largest singular triplets of a matrix from an already computed partial singular value decomposition. Our results here complement the vast literature on this topic, provide additional insight, and highlight the simplicity and the effectiveness of this procedure. We demonstrate how existing GKLB-based routines for the computation of the largest singular triplets can be easily adapted to take advantage of explicit deflation, thus making it more appealing to a wider range of users. Numerical examples are presented including an application of singular value thresholding.
Golub-Kahan-Lanczos双对角化方法中的显通缩
. 我们讨论了一个简单的,容易被忽视的,显式的压缩过程,应用于基于Golub-Kahan-Lanczos双对角化(GKLB)的方法,从已经计算的部分奇异值分解中计算矩阵的下一个最大奇异三元组集合。我们在这里的结果补充了关于这个主题的大量文献,提供了额外的见解,并强调了该过程的简单性和有效性。我们演示了现有的基于gklb的最大奇异三元组计算例程如何可以很容易地适应于利用显式压缩,从而使其对更广泛的用户更具吸引力。给出了奇异值阈值法的数值应用实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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