The Matrix Sign Function Method and the Computation of Invariant Subspaces

A perturbation analysis shows that if a numerically stable procedure is used to compute the matrix sign function, then it is competitive with conventional methods for computing invariant subspaces. Stability analysis of the Newton iteration improves an earlier result of Byers and confirms that ill-c...

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Bibliographic Details
Main Authors:	Byers, R., He, C., Mehrmann, V.
Other Authors:	TU Chemnitz, SFB 393
Format:	Others
Language:	English
Published:	Universitätsbibliothek Chemnitz 1998
Subjects:	matrix sign function invariant subspaces stability Newton iteration numerical examples MSC 65F30 MSC 65F15 ddc:510
Online Access:	http://nbn-resolving.de/urn:nbn:de:bsz:ch1-199800619 http://nbn-resolving.de/urn:nbn:de:bsz:ch1-199800619 http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/data/b025.pdf http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/data/b025.ps http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/19980061.txt

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spelling	ndltd-DRESDEN-oai-qucosa.de-bsz-ch1-1998006192018-01-26T03:23:09Z The Matrix Sign Function Method and the Computation of Invariant Subspaces Byers, R. He, C. Mehrmann, V. matrix sign function invariant subspaces stability Newton iteration numerical examples MSC 65F30 MSC 65F15 ddc:510 A perturbation analysis shows that if a numerically stable procedure is used to compute the matrix sign function, then it is competitive with conventional methods for computing invariant subspaces. Stability analysis of the Newton iteration improves an earlier result of Byers and confirms that ill-conditioned iterates may cause numerical instability. Numerical examples demonstrate the theoretical results. Universitätsbibliothek Chemnitz TU Chemnitz, SFB 393 1998-10-30 doc-type:preprint application/pdf application/postscript text/plain application/zip http://nbn-resolving.de/urn:nbn:de:bsz:ch1-199800619 urn:nbn:de:bsz:ch1-199800619 http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/data/b025.pdf http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/data/b025.ps http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/19980061.txt eng
collection	NDLTD
language	English
format	Others
sources	NDLTD
topic	matrix sign function invariant subspaces stability Newton iteration numerical examples MSC 65F30 MSC 65F15 ddc:510
spellingShingle	matrix sign function invariant subspaces stability Newton iteration numerical examples MSC 65F30 MSC 65F15 ddc:510 Byers, R. He, C. Mehrmann, V. The Matrix Sign Function Method and the Computation of Invariant Subspaces
description	A perturbation analysis shows that if a numerically stable procedure is used to compute the matrix sign function, then it is competitive with conventional methods for computing invariant subspaces. Stability analysis of the Newton iteration improves an earlier result of Byers and confirms that ill-conditioned iterates may cause numerical instability. Numerical examples demonstrate the theoretical results.
author2	TU Chemnitz, SFB 393
author_facet	TU Chemnitz, SFB 393 Byers, R. He, C. Mehrmann, V.
author	Byers, R. He, C. Mehrmann, V.
author_sort	Byers, R.
title	The Matrix Sign Function Method and the Computation of Invariant Subspaces
title_short	The Matrix Sign Function Method and the Computation of Invariant Subspaces
title_full	The Matrix Sign Function Method and the Computation of Invariant Subspaces
title_fullStr	The Matrix Sign Function Method and the Computation of Invariant Subspaces
title_full_unstemmed	The Matrix Sign Function Method and the Computation of Invariant Subspaces
title_sort	matrix sign function method and the computation of invariant subspaces
publisher	Universitätsbibliothek Chemnitz
publishDate	1998
url	http://nbn-resolving.de/urn:nbn:de:bsz:ch1-199800619 http://nbn-resolving.de/urn:nbn:de:bsz:ch1-199800619 http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/data/b025.pdf http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/data/b025.ps http://www.qucosa.de/fileadmin/data/qucosa/documents/4140/19980061.txt
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The Matrix Sign Function Method and the Computation of Invariant Subspaces

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