Spectral division methods for block generalized Schur decompositions


Journal Article

We provide a different perspective of the spectral division methods for block generalized Schur decompositions of matrix pairs. The new approach exposes more algebraic structures of the successive matrix pairs in the spectral division iterations and reveals some potential computational difficulties. We present modified algorithms to reduce the arithmetic cost by nearly 50%, remove inconsistency in spectral subspace extraction from different sides (left and right), and improve the accuracy of subspaces. In application problems that only require a single-sided deflating subspace, our algorithms can be used to obtain a posteriori estimates on the backward accuracy of the computed subspaces with little extra cost.

Full Text

Duke Authors

Cited Authors

  • Sun, X; Quintana-Ortí, ES

Published Date

  • October 1, 2004

Published In

Volume / Issue

  • 73 / 248

Start / End Page

  • 1827 - 1847

International Standard Serial Number (ISSN)

  • 0025-5718

Digital Object Identifier (DOI)

  • 10.1090/S0025-5718-04-01667-9

Citation Source

  • Scopus