About: Divide-and-conquer eigenvalue algorithm

Facets (new session)
Description
Metadata
Settings
- Rule:
- Inverse Functional Properties:
- "Same As":

About: Divide-and-conquer eigenvalue algorithm Goto Sponge NotDistinct Permalink

An Entity of Type : owl:Thing, within Data Space : el.dbpedia.org associated with source document(s)

Divide-and-conquer eigenvalue algorithms are a class of eigenvalue algorithms for Hermitian or real symmetric matrices that have recently (circa 1990s) become competitive in terms of stability and efficiency with more traditional algorithms such as the QR algorithm. The basic concept behind these algorithms is the divide-and-conquer approach from computer science. An eigenvalue problem is divided into two problems of roughly half the size, each of these are solved recursively, and the eigenvalues of the original problem are computed from the results of these smaller problems.

Attributes	Values
rdfs:label	Divide-and-conquer eigenvalue algorithm (en)
rdfs:comment	Divide-and-conquer eigenvalue algorithms are a class of eigenvalue algorithms for Hermitian or real symmetric matrices that have recently (circa 1990s) become competitive in terms of stability and efficiency with more traditional algorithms such as the QR algorithm. The basic concept behind these algorithms is the divide-and-conquer approach from computer science. An eigenvalue problem is divided into two problems of roughly half the size, each of these are solved recursively, and the eigenvalues of the original problem are computed from the results of these smaller problems. (en)
sameAs	Divide-and-conquer eigenvalue algorithm
dbp:wikiPageUsesTemplate	dbt:Citation dbt:Citation_needed dbt:Cite_journal dbt:Numerical_linear_algebra
Subject	Divide-and-conquer algorithms Numerical linear algebra
thumbnail	wiki-commons:Special:FilePath/Almost_block_diagonal.png?width=300
foaf:depiction
gold:hypernym	Algorithms
prov:wasDerivedFrom	http://en.wikipedia.org/wiki/Divide-and-conquer_eigenvalue_algorithm?oldid=1063206300&ns=0
Wikipage page ID	1103352 (xsd:integer)
page length (characters) of wiki page	10541 (xsd:nonNegativeInteger)
Wikipage revision ID	1063206300 (xsd:integer)
Link from a Wikipage to another Wikipage	Floating-point arithmetic Nonlinear system Numerical stability Numerische Mathematik Arnoldi iteration Big O notation Block matrix Divide-and-conquer algorithms Numerical linear algebra Divide-and-conquer algorithm QR algorithm Householder transformation Linear algebra Tridiagonal matrix Algorithmic complexity Computer science Eigenvalue algorithm Eigenvalues and eigenvectors Hermitian matrix Newton's method Parallel algorithm Society for Industrial and Applied Mathematics Symmetric matrix Diagonalizable matrix LAPACK Master theorem (analysis of algorithms) Rank (linear algebra) Algebraic fraction Real number Recurrence relation Recursion
has abstract	Divide-and-conquer eigenvalue algorithms are a class of eigenvalue algorithms for Hermitian or real symmetric matrices that have recently (circa 1990s) become competitive in terms of stability and efficiency with more traditional algorithms such as the QR algorithm. The basic concept behind these algorithms is the divide-and-conquer approach from computer science. An eigenvalue problem is divided into two problems of roughly half the size, each of these are solved recursively, and the eigenvalues of the original problem are computed from the results of these smaller problems. Here we present the simplest version of a divide-and-conquer algorithm, similar to the one originally proposed by Cuppen in 1981. Many details that lie outside the scope of this article will be omitted; however, without considering these details, the algorithm is not fully stable. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Divide-and-conquer_eigenvalue_algorithm
is Link from a Wikipage to another Wikipage of	Divide and conquer List of numerical analysis topics Eigendecomposition of a matrix Eigenvalue algorithm Lanczos algorithm
is foaf:primaryTopic of	http://en.wikipedia.org/wiki/Divide-and-conquer_eigenvalue_algorithm

Faceted Search & Find service v1.17_git151 as of Feb 20 2025

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Nov 11 2024, on Linux (x86_64-ubuntu_focal-linux-gnu), Single-Server Edition (72 GB total memory, 1 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software