Cubically Convergent Iterations for Invariant Subspace Computation

Date

2004

Authors

Absil, P-A
Sepulchre, R
Van Dooren, P
Mahony, Robert

Journal Title

Journal ISSN

Volume Title

Publisher

Society for Industrial and Applied Mathematics

Abstract

We propose a Newton-like iteration that evolves on the set of fixed dimensional subspaces of ℝn and converges locally cubically to the invariant subspaces of a symmetric matrix. This iteration is compared in terms of numerical cost and global behavior w

Description

Keywords

Keywords: Data coding; Jacobi-Davidson method; Newton equations; Normalization; Algorithms; Computational methods; Data compression; Eigenvalues and eigenfunctions; Heuristic methods; Mathematical operators; Matrix algebra; Optimization; Riccati equations; Set theo Cubic convergence; Global convergence; Grassmann manifold; Invariant subspace; Inverse iteration; Newton method; Rayleigh quotient; Symmetric eigenproblem

Citation

URI

http://hdl.handle.net/1885/77992

Collections

ANU Research Publications

Source

SIAM Journal on Matrix Analysis and Applications

Type

Journal article

Book Title

Entity type

Access Statement

License Rights

DOI

10.1137/S0895479803422002

Restricted until

DSpace software copyright © 2002-2026 LYRASIS