Small singular values can increase in lower precision
From MaRDI portal
Publication:6592219
DOI10.1137/23m1557209zbMATH Open1545.65153MaRDI QIDQ6592219
Petros Drineas, Christos Boutsikas, Ilse C. F. Ipsen
Publication date: 24 August 2024
Published in: SIAM Journal on Matrix Analysis and Applications (Search for Journal in Brave)
perturbation theoryeigenvaluessingular valuesLoewner partial orderingarithmetic precisionreal symmetric positive semi-definite matrices
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Inequalities involving eigenvalues and eigenvectors (15A42) Eigenvalues, singular values, and eigenvectors (15A18)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A note on a lower bound for the smallest singular value
- A Gershgorin-type lower bound for the smallest singular value
- A second order perturbation expansion for small singular values
- Inversion of extremely ill-conditioned matrices in floating-point
- Perturbation of the SVD in the presence of small singular values
- Estimation of \(\| A ^{-1} \|_\infty \) and the smallest singular value
- A lower bound for the smallest singular value
- A lower bound for the smallest singular value of a matrix
- Further lower bounds for the smallest singular value
- Schur complement-based infinity norm bounds for the inverse of SDD matrices
- On some lower bounds for smallest singular value of matrices
- Schur complement-based infinity norm bounds for the inverse of \(DSDD\) matrices
- A lower bound for the smallest singular value
- Two new lower bounds for the smallest singular value
- Calculating the Singular Values and Pseudo-Inverse of a Matrix
- Lower bounds for the smallest singular values of generalized asymptotic diagonal dominant matrices
This page was built for publication: Small singular values can increase in lower precision
