Improved bound for rank revealing LU factorizations

Tsung Min Hwang*, Wen-Wei Lin, Daniel Pierce

*Corresponding author for this work

研究成果: Article同行評審

12 引文 斯高帕斯(Scopus)


In many applications it is necessary to determine the rank (or numerical rank) of a matrix. Many of these situations involve matrices that are very large order or that are sparse or that may undergo some form of modification (rank-k update, row or column appended or removed). In these cases the singular value decomposition's cost may be prohibitively high or the decomposition may not be computationally feasible (especially for large sparse problems). We thus examine the theoretical merits of rank revealing LU (RRLU) factorizations. We find that in those cases where the nullity is small and the gap is well defined, an RRLU factorization could be a very useful tool.

頁(從 - 到)173-186
期刊Linear Algebra and Its Applications
出版狀態Published - 1 一月 1997

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