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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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Bibliographic Details
Published in:Special matrices 2024-04, Vol.12 (1), p.1275-1294
Main Author: Dax, Achiya
Format: Article
Language:English
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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.”
ISSN:2300-7451
2300-7451
DOI:10.1515/spma-2024-0002