Highly accurate symmetric eigenvalue decomposition and hyperbolic SVD

DOI10.1016/S0024-3795(02)00516-5zbMath1030.65026OpenAlexW2009871339MaRDI QIDQ1855448

Ivan Slapničar

Publication date: 5 February 2003

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0024-3795(02)00516-5

zbMATH Keywords

algorithmnumerical examplesJacobi methodsymmetric eigenvalue problemhigh relative accuracyhyperbolic singular value decompositionrelative perturbation theorysymmetric indefinition decomposition

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical solutions to overdetermined systems, pseudoinverses (65F20)

Related Items (10)

A note on the hyperbolic singular value decomposition without hyperexchange matrices ⋮ Three-level parallel J-Jacobi algorithms for Hermitian matrices ⋮ Full block \(J\)-Jacobi method for Hermitian matrices ⋮ A GPU-based hyperbolic SVD algorithm ⋮ Novel modifications of parallel Jacobi algorithms ⋮ Convergence to diagonal form of block Jacobi-type methods ⋮ Block-oriented \(J\)-Jacobi methods for Hermitian matrices ⋮ On the global convergence of the block Jacobi method for the positive definite generalized eigenvalue problem ⋮ Numerical methods for accurate computation of the eigenvalues of Hermitian matrices and the singular values of general matrices ⋮ Implicit standard Jacobi gives high relative accuracy

Uses Software

• LAPACK

Cites Work

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