An efficient algorithm for the minimal least squares solution of linear systems with indefinite symmetric matrices
From MaRDI portal
Publication:6556719
DOI10.1016/J.CAM.2024.115783MaRDI QIDQ6556719
Ibai Coria, G. Urkullu, Haritz Uriarte, Igor Fernández De Bustos
Publication date: 17 June 2024
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
symmetric indefinite matrixleast squares solutionJacobi rotationsdiagonal pivoting method\(LDL^t\) factorizationBunch-Kaufman
Cites Work
- Title not available (Why is that?)
- An alternative full-pivoting algorithm for the factorization of indefinite symmetric matrices
- An efficient LDU algorithm for the minimal least squares solution of linear systems
- Fehleranalyse für die Gauß-Elimination zur Berechnung der Lösung minimaler Länge
- A geometric analysis of Gaussian elimination. II
- The growth factor and efficiency of Gaussian elimination with rook pivoting
- The Rook's pivoting strategy
- The Growth-Factor Bound for the Bunch-Kaufman Factorization Is Tight
- Stability of the Diagonal Pivoting Method with Partial Pivoting
- A Note on the Generation of Random Normal Deviates
- The Null Space Problem I. Complexity
- Error Analysis of Direct Methods of Matrix Inversion
- The Efficient Generation of Random Orthogonal Matrices with an Application to Condition Estimators
- Some Stable Methods for Calculating Inertia and Solving Symmetric Linear Systems
- Mersenne twister
- Accurate Symmetric Indefinite Linear Equation Solvers
- Random Matrices Generating Large Growth in LU Factorization with Pivoting
- The least squares problem and pseudo-inverses
- Direct Methods for Solving Symmetric Indefinite Systems of Linear Equations
This page was built for publication: An efficient algorithm for the minimal least squares solution of linear systems with indefinite symmetric matrices
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6556719)