期刊
APPLIED MATHEMATICS LETTERS
卷 112, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.aml.2020.106706
关键词
Low-rank matrix; Low-rank eigenvalue problem; Large-scale eigenproblem; Jordan decomposition; Jordan vector; Schur decomposition
资金
- Fundamental Research Funds for the Central Universities of China [2019XKQYMS89]
The paper explores the eigenproblem on large and low-rank matrices, focusing on the relations between the Jordan decomposition and the Schur decomposition of small and large matrices. The proposed construction methods are not only theoretical but also practical, as demonstrated by numerical experiments.
In this paper, we are interested in the eigenproblem on the large and low-rank matrix S = AB(H), where A, B is an element of C-nxr are of full column rank and r << n. To the best of our knowledge, there are no results on the relations between the Jordan decomposition and the Schur decomposition of B(H)A and those of AB(H). Some known results are only on characteristic polynomials, elementary divisors, and Jordan blocks of AB(H), and are purely theoretical and are not easy to use for computational purposes. Based on the Jordan decomposition and the Schur decomposition of the small matrix B(H)A is an element of C-rxr, we consider how to derive those of the large matrix A(H)B is an element of C-nxn in this work. The construction methods proposed are not only theoretical but also practical. Numerical experiments show the effectiveness of our theoretical results. (c) 2020 Elsevier Ltd. All rights reserved.
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