|
|
|
|
LEADER |
01725nab a2200193 c 4500 |
001 |
22-ch1-199801313 |
007 |
cr |
008 |
1998 eng |
037 |
|
|
|a urn:nbn:de:bsz:ch1-199801313
|
041 |
|
|
|a eng
|
082 |
|
|
|a 510
|
100 |
|
|
|a Benhammouda, B.
|
245 |
|
|
|a Rank-revealing top-down ULV factorizations
|
264 |
|
|
|a Chemnitz
|b Technische Universität Chemnitz
|
533 |
|
|
|a Online-Ausg.
|d 1998
|e Online-Ressource (Text)
|f Universitätsbibliothek Chemnitz
|
520 |
|
|
|a Rank-revealing ULV and URV factorizations are useful tools to determine the rank and to compute bases for null-spaces of a matrix. However, in the practical ULV (resp. URV ) factorization each left (resp. right) null vector is recomputed from its corresponding right (resp. left) null vector via triangular solves. Triangular solves are required at initial factorization, refinement and updating. As a result, algorithms based on these factorizations may be expensive, especially on parallel computers where triangular solves are expensive. In this paper we propose an alternative approach. Our new rank-revealing ULV factorization, which we call ¨top-down¨ ULV factorization ( TDULV -factorization) is based on right null vectors of lower triangular matrices and therefore no triangular solves are required. Right null vectors are easy to estimate accurately using condition estimators such as incremental condition estimator (ICE). The TDULV factorization is shown to be equivalent to the URV factorization with the advantage of circumventing triangular solves.
|
650 |
|
|
|a Msc 65F15
|
856 |
4 |
0 |
|q text/html
|u https://nbn-resolving.org/urn:nbn:de:bsz:ch1-199801313
|z Online-Zugriff
|
980 |
|
|
|a ch1-199801313
|b 22
|c sid-22-col-qucosa
|
SOLR
_version_ |
1794756112577200128 |
author |
Benhammouda, B. |
author_facet |
Benhammouda, B. |
author_role |
|
author_sort |
Benhammouda, B. |
author_variant |
b b bb |
building |
Library A |
collection |
sid-22-col-qucosa |
contents |
Rank-revealing ULV and URV factorizations are useful tools to determine the rank and to compute bases for null-spaces of a matrix. However, in the practical ULV (resp. URV ) factorization each left (resp. right) null vector is recomputed from its corresponding right (resp. left) null vector via triangular solves. Triangular solves are required at initial factorization, refinement and updating. As a result, algorithms based on these factorizations may be expensive, especially on parallel computers where triangular solves are expensive. In this paper we propose an alternative approach. Our new rank-revealing ULV factorization, which we call ¨top-down¨ ULV factorization ( TDULV -factorization) is based on right null vectors of lower triangular matrices and therefore no triangular solves are required. Right null vectors are easy to estimate accurately using condition estimators such as incremental condition estimator (ICE). The TDULV factorization is shown to be equivalent to the URV factorization with the advantage of circumventing triangular solves. |
dewey-full |
510 |
dewey-hundreds |
500 - Natural sciences and mathematics |
dewey-ones |
510 - Mathematics |
dewey-raw |
510 |
dewey-search |
510 |
dewey-sort |
3510 |
dewey-tens |
510 - Mathematics |
facet_avail |
Online, Free |
finc_class_facet |
Mathematik |
fincclass_txtF_mv |
science-mathematics |
format |
ElectronicSerialComponentPart |
format_access_txtF_mv |
Article, E-Article |
format_de105 |
Ebook |
format_de14 |
Article, E-Article |
format_de15 |
Article, E-Article |
format_del152 |
Buch |
format_detail_txtF_mv |
text-online-journal-child |
format_dezi4 |
Journal |
format_finc |
Article, E-Article |
format_legacy |
ElectronicArticle |
format_legacy_nrw |
Article, E-Article |
format_nrw |
Article, E-Article |
format_strict_txtF_mv |
E-Article |
geogr_code |
not assigned |
geogr_code_person |
not assigned |
id |
22-ch1-199801313 |
illustrated |
Not Illustrated |
imprint |
Chemnitz, Technische Universität Chemnitz |
imprint_str_mv |
Online-Ausg.: 1998 |
institution |
DE-105, DE-Gla1, DE-Brt1, DE-D161, DE-540, DE-Pl11, DE-Rs1, DE-Bn3, DE-Zi4, DE-Zwi2, DE-D117, DE-Mh31, DE-D275, DE-Ch1, DE-15, DE-D13, DE-L242, DE-L229, DE-L328 |
is_hierarchy_id |
|
is_hierarchy_title |
|
language |
English |
last_indexed |
2024-03-28T08:00:08.545Z |
match_str |
benhammouda1998rankrevealingtopdownulvfactorizations |
mega_collection |
Qucosa |
publishDate |
|
publishDateSort |
1998 |
publishPlace |
Chemnitz |
publisher |
Technische Universität Chemnitz |
record_format |
marcfinc |
record_id |
ch1-199801313 |
recordtype |
marcfinc |
rvk_facet |
No subject assigned |
source_id |
22 |
spelling |
Benhammouda, B., Rank-revealing top-down ULV factorizations, Chemnitz Technische Universität Chemnitz, Online-Ausg. 1998 Online-Ressource (Text) Universitätsbibliothek Chemnitz, Rank-revealing ULV and URV factorizations are useful tools to determine the rank and to compute bases for null-spaces of a matrix. However, in the practical ULV (resp. URV ) factorization each left (resp. right) null vector is recomputed from its corresponding right (resp. left) null vector via triangular solves. Triangular solves are required at initial factorization, refinement and updating. As a result, algorithms based on these factorizations may be expensive, especially on parallel computers where triangular solves are expensive. In this paper we propose an alternative approach. Our new rank-revealing ULV factorization, which we call ¨top-down¨ ULV factorization ( TDULV -factorization) is based on right null vectors of lower triangular matrices and therefore no triangular solves are required. Right null vectors are easy to estimate accurately using condition estimators such as incremental condition estimator (ICE). The TDULV factorization is shown to be equivalent to the URV factorization with the advantage of circumventing triangular solves., Msc 65F15, text/html https://nbn-resolving.org/urn:nbn:de:bsz:ch1-199801313 Online-Zugriff |
spellingShingle |
Benhammouda, B., Rank-revealing top-down ULV factorizations, Rank-revealing ULV and URV factorizations are useful tools to determine the rank and to compute bases for null-spaces of a matrix. However, in the practical ULV (resp. URV ) factorization each left (resp. right) null vector is recomputed from its corresponding right (resp. left) null vector via triangular solves. Triangular solves are required at initial factorization, refinement and updating. As a result, algorithms based on these factorizations may be expensive, especially on parallel computers where triangular solves are expensive. In this paper we propose an alternative approach. Our new rank-revealing ULV factorization, which we call ¨top-down¨ ULV factorization ( TDULV -factorization) is based on right null vectors of lower triangular matrices and therefore no triangular solves are required. Right null vectors are easy to estimate accurately using condition estimators such as incremental condition estimator (ICE). The TDULV factorization is shown to be equivalent to the URV factorization with the advantage of circumventing triangular solves., Msc 65F15 |
title |
Rank-revealing top-down ULV factorizations |
title_auth |
Rank-revealing top-down ULV factorizations |
title_full |
Rank-revealing top-down ULV factorizations |
title_fullStr |
Rank-revealing top-down ULV factorizations |
title_full_unstemmed |
Rank-revealing top-down ULV factorizations |
title_short |
Rank-revealing top-down ULV factorizations |
title_sort |
rank-revealing top-down ulv factorizations |
title_unstemmed |
Rank-revealing top-down ULV factorizations |
topic |
Msc 65F15 |
topic_facet |
Msc 65F15 |
url |
https://nbn-resolving.org/urn:nbn:de:bsz:ch1-199801313 |
urn |
urn:nbn:de:bsz:ch1-199801313 |
work_keys_str_mv |
AT benhammoudab rankrevealingtopdownulvfactorizations |