Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs

Detalhes bibliográficos
Autores: Luengo García, David|||0000-0001-7407-3630, Monzón García, Sandra, Artés Rodríguez, Antonio
Formato: artículo
Fecha de publicación:2012
País:España
Recursos:Universidad Politécnica de Madrid
Repositorio:Archivo Digital UPM
OAI Identifier:oai:oa.upm.es:22660
Acesso em linha:https://oa.upm.es/22660/
Access Level:acceso abierto
Palavra-chave:Linear blind inverse problems
Sparse signals
Line orientation clustering
MIMO systems
Neyman–Pearson hypothesis test
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spelling Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputsLuengo García, David|||0000-0001-7407-3630Monzón García, SandraArtés Rodríguez, AntonioLinear blind inverse problemsSparse signalsLine orientation clusteringMIMO systemsNeyman–Pearson hypothesis test20122012-06-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articlehttps://oa.upm.es/22660/reponame:Archivo Digital UPMinstname:Universidad Politécnica de MadridInglésenopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:oa.upm.es:226602026-06-21T12:45:07Z
dc.title.none.fl_str_mv Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs
title Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs
spellingShingle Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs
Luengo García, David|||0000-0001-7407-3630
Linear blind inverse problems
Sparse signals
Line orientation clustering
MIMO systems
Neyman–Pearson hypothesis test
title_short Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs
title_full Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs
title_fullStr Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs
title_full_unstemmed Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs
title_sort Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs
dc.creator.none.fl_str_mv Luengo García, David|||0000-0001-7407-3630
Monzón García, Sandra
Artés Rodríguez, Antonio
author Luengo García, David|||0000-0001-7407-3630
author_facet Luengo García, David|||0000-0001-7407-3630
Monzón García, Sandra
Artés Rodríguez, Antonio
author_role author
author2 Monzón García, Sandra
Artés Rodríguez, Antonio
author2_role author
author
dc.subject.none.fl_str_mv Linear blind inverse problems
Sparse signals
Line orientation clustering
MIMO systems
Neyman–Pearson hypothesis test
topic Linear blind inverse problems
Sparse signals
Line orientation clustering
MIMO systems
Neyman–Pearson hypothesis test
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-06-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://oa.upm.es/22660/
url https://oa.upm.es/22660/
dc.language.none.fl_str_mv Inglés
en
language_invalid_str_mv Inglés
en
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Archivo Digital UPM
instname:Universidad Politécnica de Madrid
instname_str Universidad Politécnica de Madrid
reponame_str Archivo Digital UPM
collection Archivo Digital UPM
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869417806291795968
score 15,301603

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