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The smallest singular value anomaly: The reasons behind sharp anomaly
Let be an arbitrary matrix in which the number of rows, , is considerably larger than the number of columns, . Let the submatrix , be composed from the first rows of , and let denote the smallest singular value of . Recently, we observed that the first part of this sequence, , is descending, while t...
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Published in: | Special matrices 2024-04, Vol.12 (1), p.1275-1294 |
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Main Author: | |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Let
be an arbitrary matrix in which the number of rows,
, is considerably larger than the number of columns,
. Let the submatrix
, be composed from the first
rows of
, and let
denote the smallest singular value of
. Recently, we observed that the first part of this sequence,
, is descending, while the second part,
, is ascending. This property is called “the smallest singular value anomaly.” In this article, we expose another interesting feature of this sequence. It is shown that certain types of matrices possess the sharp anomaly phenomenon: First, when
is considerably smaller than
, the value of
decreases rather slowly. Then, as
approaches
from below, there is fast reduction in the value of
, making
much smaller than
. Yet, once
passes
, the situation is reversed and
increases rapidly. Finally, when
moves away from
, the rate of increase slows down. The article illustrates this behavior and explores its reasons. It is shown that the sharp anomaly phenomenon occurs in matrices with “scattering rows.” |
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ISSN: | 2300-7451 2300-7451 |
DOI: | 10.1515/spma-2024-0002 |