Impact of higher-order statistics on adaptive algorithms for blind source separation

Detalhes bibliográficos
Autor(a) principal: Cavalcante, Charles Casimiro
Data de Publicação: 2004
Outros Autores: Romano, João Marcos Travassos
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
Texto Completo: http://www.repositorio.ufc.br/handle/riufc/69699
Resumo: The paper is devoted to present an analysis of the impact of higher order statistics (HOS) in adaptive blind source separation criteria. Despite the well known fact that they are necessary to provide source separation in a general framework, their impact on the performance of adaptive solutions is a still open research field. The approach of probability density function (pdf) recovering is used. In order to verify the analysis, two constrained adaptive algorithms are investigated. Namely, the multiuser kurtosis algorithm (MUK) and the multiuser constrained fitting probability density function algorithm (MU-CFPA) are used due to the desired characteristics of different HOS involved in their design. Simulation results are carried out to basis our analysis.
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spelling Impact of higher-order statistics on adaptive algorithms for blind source separationProcessamento de sinaisSeparação cega de fontesThe paper is devoted to present an analysis of the impact of higher order statistics (HOS) in adaptive blind source separation criteria. Despite the well known fact that they are necessary to provide source separation in a general framework, their impact on the performance of adaptive solutions is a still open research field. The approach of probability density function (pdf) recovering is used. In order to verify the analysis, two constrained adaptive algorithms are investigated. Namely, the multiuser kurtosis algorithm (MUK) and the multiuser constrained fitting probability density function algorithm (MU-CFPA) are used due to the desired characteristics of different HOS involved in their design. Simulation results are carried out to basis our analysis.Workshop on Signal Processing Advances in Wireless Communications2022-12-12T14:03:45Z2022-12-12T14:03:45Z2004info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectapplication/pdfCAVALCANTE, C. C.; ROMANO, J .M. T. Impact of higher-order statistics on adaptive algorithms for blind source separation. In: WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, 5., 2004, Lisboa. Anais... Lisboa: IEEE, 2004. p. 170-174.http://www.repositorio.ufc.br/handle/riufc/69699Cavalcante, Charles CasimiroRomano, João Marcos Travassosengreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccess2022-12-12T14:03:45Zoai:repositorio.ufc.br:riufc/69699Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2024-09-11T19:01:31.838262Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Impact of higher-order statistics on adaptive algorithms for blind source separation
title Impact of higher-order statistics on adaptive algorithms for blind source separation
spellingShingle Impact of higher-order statistics on adaptive algorithms for blind source separation
Cavalcante, Charles Casimiro
Processamento de sinais
Separação cega de fontes
title_short Impact of higher-order statistics on adaptive algorithms for blind source separation
title_full Impact of higher-order statistics on adaptive algorithms for blind source separation
title_fullStr Impact of higher-order statistics on adaptive algorithms for blind source separation
title_full_unstemmed Impact of higher-order statistics on adaptive algorithms for blind source separation
title_sort Impact of higher-order statistics on adaptive algorithms for blind source separation
author Cavalcante, Charles Casimiro
author_facet Cavalcante, Charles Casimiro
Romano, João Marcos Travassos
author_role author
author2 Romano, João Marcos Travassos
author2_role author
dc.contributor.author.fl_str_mv Cavalcante, Charles Casimiro
Romano, João Marcos Travassos
dc.subject.por.fl_str_mv Processamento de sinais
Separação cega de fontes
topic Processamento de sinais
Separação cega de fontes
description The paper is devoted to present an analysis of the impact of higher order statistics (HOS) in adaptive blind source separation criteria. Despite the well known fact that they are necessary to provide source separation in a general framework, their impact on the performance of adaptive solutions is a still open research field. The approach of probability density function (pdf) recovering is used. In order to verify the analysis, two constrained adaptive algorithms are investigated. Namely, the multiuser kurtosis algorithm (MUK) and the multiuser constrained fitting probability density function algorithm (MU-CFPA) are used due to the desired characteristics of different HOS involved in their design. Simulation results are carried out to basis our analysis.
publishDate 2004
dc.date.none.fl_str_mv 2004
2022-12-12T14:03:45Z
2022-12-12T14:03:45Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv CAVALCANTE, C. C.; ROMANO, J .M. T. Impact of higher-order statistics on adaptive algorithms for blind source separation. In: WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, 5., 2004, Lisboa. Anais... Lisboa: IEEE, 2004. p. 170-174.
http://www.repositorio.ufc.br/handle/riufc/69699
identifier_str_mv CAVALCANTE, C. C.; ROMANO, J .M. T. Impact of higher-order statistics on adaptive algorithms for blind source separation. In: WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, 5., 2004, Lisboa. Anais... Lisboa: IEEE, 2004. p. 170-174.
url http://www.repositorio.ufc.br/handle/riufc/69699
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Workshop on Signal Processing Advances in Wireless Communications
publisher.none.fl_str_mv Workshop on Signal Processing Advances in Wireless Communications
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
collection Repositório Institucional da Universidade Federal do Ceará (UFC)
repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv bu@ufc.br || repositorio@ufc.br
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