{"id":{"repo_id":"brazil-uerj","oai_identifier":"oai:pantheon.ufrj.br:11422/6429"},"canonical_url":"https://search.dev.ndltd.org/etd/brazil-uerj/oai:pantheon.ufrj.br:11422/6429","repository":{"repo_id":"brazil-uerj","name":"Brazil UERJ","base_url":"https://pantheon.ufrj.br/oai/request"},"display":{"title":"Uma investigação sobre métodos de separação cega de fontes sonoras envolvendo representações não-negativas e diversidade espacial","abstract":"The problem of blind source separation finds many applications across different areas, thus justifying the ever increasing number of works in this topic. This work focuses on studying this problem for sound sources, employing non-negative signals’ representations, while also taking advantage of the spatial diversity induced by the use of multiple channels; this particular feature has recently opened up new research directions regarding the proper modeling of multichannel source separation This work studies two different algorithms: NMF-SCM (sound source separation using non-negative matrix factorization and direction-of-arrival-based spatial covariance model), whose model represents the state of the art, taking in consideration not only the characteristics of the sources but also the enviroment into which they were captured on; and NTF (non-negative tensor factorization), whose simplified model is the multichannel equivalent of NMF (non-negative matrix factorization). During the development of this work both algorithms were implemented. A vectorized and parallelized NMF-SCM implementation is presented; and some improvements are proposed to the NTF algorithm, as well as a method for blind determination of the number of sources in multichannel mixtures.","abstract_html":"The problem of blind source separation finds many applications across different areas, thus justifying the ever increasing number of works in this topic. This work focuses on studying this problem for sound sources, employing non-negative signals’ representations, while also taking advantage of the spatial diversity induced by the use of multiple channels; this particular feature has recently opened up new research directions regarding the proper modeling of multichannel source separation This work studies two different algorithms: NMF-SCM (sound source separation using non-negative matrix factorization and direction-of-arrival-based spatial covariance model), whose model represents the state of the art, taking in consideration not only the characteristics of the sources but also the enviroment into which they were captured on; and NTF (non-negative tensor factorization), whose simplified model is the multichannel equivalent of NMF (non-negative matrix factorization). During the development of this work both algorithms were implemented. A vectorized and parallelized NMF-SCM implementation is presented; and some improvements are proposed to the NTF algorithm, as well as a method for blind determination of the number of sources in multichannel mixtures.","abstract_has_math":false,"creators":["Romero, Claudio"],"institution":"Universidade Federal do Rio de Janeiro","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Martins, Wallace Alves"],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-03","date_published":"2017-03","updated_at":"2026-07-24T01:16:21Z","subjects":["Engenharia elétrica","Fontes sonoras - Métodos de separação cega."],"languages":["por"],"rights":["Acesso Aberto"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11422/6429","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Martins, Wallace Alves"]},{"key":"dc:creator","label":"Author","values":["Romero, Claudio"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2019-02-08T15:11:15Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-05-16T03:03:47Z"]},{"key":"dc:date.issued","label":"Date","values":["2017-03"]},{"key":"dc:publisher","label":"Institution","values":["Universidade Federal do Rio de Janeiro"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia"]},{"key":"dc:type","label":"Dc Type","values":["Dissertação"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engenharia elétrica","Fontes sonoras - Métodos de separação cega."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["por"]},{"key":"dc:rights","label":"Dc Rights","values":["Acesso Aberto"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11422/6429"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The problem of blind source separation finds many applications across different areas, thus justifying the ever increasing number of works in this topic. 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