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2020 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2020
The equation $A x=0$ tells us that x is perpendicular to every row of $A-$ and therefore to the whole row space of A. This is fundamental, but singular vectors v in the row space do more. (1) the v’s are orthogonal (2) the vectors $u=A v$ are also orthogonal (in the column space of A).
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The equation $A x=0$ tells us that x is perpendicular to every row of $A-$ and therefore to the whole row space of A. This is fundamental, but singular vectors v in the row space do more. (1) the v’s are orthogonal (2) the vectors $u=A v$ are also orthogonal (in the column space of A).
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Annals of Combinatorics, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Orthogonality and retract orthogonality of operations
2018Summary: In this article, we study connections between orthogonality and retract orthogonality of operations. We prove that if a tuple of operations is retractly orthogonal, then it is orthogonal. However, orthogonality of operations doesn't provide their retract orthogonality.
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ON THE TRUE INTERVAL OF ORTHOGONALITY FOR ORTHOGONAL POLYNOMIALS
The Quarterly Journal of Mathematics, 1970openaire +2 more sources
On Birkhoff Orthogonality and Isosceles Orthogonality in Normed Linear Spaces
Aequationes Mathematicae, 2012Javier Alonso, Senlin Wu
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Two Metrics for Measuring Orthogonality for Two-Dimensional Chromatography
Journal of Chromatography A, 2019John Mommers, Sjoerd van der Wal
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On Three Concepts of Orthogonality in Hilbert C*-Modules
Linear and Multilinear Algebra, 2015Rajna Rajic, Ljiljana Arambašić
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