A Lempel-Ziv like approach for signal classification

Detalhes bibliográficos
Autor(a) principal: Montalvão,J.
Data de Publicação: 2014
Outros Autores: Canuto,J.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: TEMA (Sociedade Brasileira de Matemática Aplicada e Computacional. Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-84512014000200009
Resumo: In this paper, the seminal method proposed by Abraham Lempel and Jacob Ziv, aimed at the complexity analysis of sequences of symbols, was modified to compare similarities between two sequences. This modification allowed the creation of a new criterion which can replace likelihood in some pattern recognition applications. Moreover, to allow for analysis and comparison of multivariate continuously valued patterns, we also present a simple adaptation of the Lempel-Ziv's method to time-sampled signals. To illustrate the usefulness of these proposed tools, two sets of experimental results are presented, namely: one on speaker identity verification (biometrics) and another on healthcare signal detection. Both experiments yield promising performances. Moreover, as compared to a conventional pattern recognition method, the new approach provided better performances in terms of Equal Error Ratio in speaker verification experiments.
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spelling A Lempel-Ziv like approach for signal classificationsignal analysisno a prioriLempel-Ziv complexityIn this paper, the seminal method proposed by Abraham Lempel and Jacob Ziv, aimed at the complexity analysis of sequences of symbols, was modified to compare similarities between two sequences. This modification allowed the creation of a new criterion which can replace likelihood in some pattern recognition applications. Moreover, to allow for analysis and comparison of multivariate continuously valued patterns, we also present a simple adaptation of the Lempel-Ziv's method to time-sampled signals. To illustrate the usefulness of these proposed tools, two sets of experimental results are presented, namely: one on speaker identity verification (biometrics) and another on healthcare signal detection. Both experiments yield promising performances. Moreover, as compared to a conventional pattern recognition method, the new approach provided better performances in terms of Equal Error Ratio in speaker verification experiments.Sociedade Brasileira de Matemática Aplicada e Computacional2014-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-84512014000200009TEMA (São Carlos) v.15 n.2 2014reponame:TEMA (Sociedade Brasileira de Matemática Aplicada e Computacional. Online)instname:Sociedade Brasileira de Matemática Aplicada e Computacionalinstacron:SBMAC10.5540/tema.2014.015.02.0223info:eu-repo/semantics/openAccessMontalvão,J.Canuto,J.eng2014-09-10T00:00:00Zoai:scielo:S2179-84512014000200009Revistahttp://www.scielo.br/temaPUBhttps://old.scielo.br/oai/scielo-oai.phpcastelo@icmc.usp.br2179-84511677-1966opendoar:2014-09-10T00:00TEMA (Sociedade Brasileira de Matemática Aplicada e Computacional. Online) - Sociedade Brasileira de Matemática Aplicada e Computacionalfalse
dc.title.none.fl_str_mv A Lempel-Ziv like approach for signal classification
title A Lempel-Ziv like approach for signal classification
spellingShingle A Lempel-Ziv like approach for signal classification
Montalvão,J.
signal analysis
no a priori
Lempel-Ziv complexity
title_short A Lempel-Ziv like approach for signal classification
title_full A Lempel-Ziv like approach for signal classification
title_fullStr A Lempel-Ziv like approach for signal classification
title_full_unstemmed A Lempel-Ziv like approach for signal classification
title_sort A Lempel-Ziv like approach for signal classification
author Montalvão,J.
author_facet Montalvão,J.
Canuto,J.
author_role author
author2 Canuto,J.
author2_role author
dc.contributor.author.fl_str_mv Montalvão,J.
Canuto,J.
dc.subject.por.fl_str_mv signal analysis
no a priori
Lempel-Ziv complexity
topic signal analysis
no a priori
Lempel-Ziv complexity
description In this paper, the seminal method proposed by Abraham Lempel and Jacob Ziv, aimed at the complexity analysis of sequences of symbols, was modified to compare similarities between two sequences. This modification allowed the creation of a new criterion which can replace likelihood in some pattern recognition applications. Moreover, to allow for analysis and comparison of multivariate continuously valued patterns, we also present a simple adaptation of the Lempel-Ziv's method to time-sampled signals. To illustrate the usefulness of these proposed tools, two sets of experimental results are presented, namely: one on speaker identity verification (biometrics) and another on healthcare signal detection. Both experiments yield promising performances. Moreover, as compared to a conventional pattern recognition method, the new approach provided better performances in terms of Equal Error Ratio in speaker verification experiments.
publishDate 2014
dc.date.none.fl_str_mv 2014-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-84512014000200009
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-84512014000200009
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.5540/tema.2014.015.02.0223
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Matemática Aplicada e Computacional
publisher.none.fl_str_mv Sociedade Brasileira de Matemática Aplicada e Computacional
dc.source.none.fl_str_mv TEMA (São Carlos) v.15 n.2 2014
reponame:TEMA (Sociedade Brasileira de Matemática Aplicada e Computacional. Online)
instname:Sociedade Brasileira de Matemática Aplicada e Computacional
instacron:SBMAC
instname_str Sociedade Brasileira de Matemática Aplicada e Computacional
instacron_str SBMAC
institution SBMAC
reponame_str TEMA (Sociedade Brasileira de Matemática Aplicada e Computacional. Online)
collection TEMA (Sociedade Brasileira de Matemática Aplicada e Computacional. Online)
repository.name.fl_str_mv TEMA (Sociedade Brasileira de Matemática Aplicada e Computacional. Online) - Sociedade Brasileira de Matemática Aplicada e Computacional
repository.mail.fl_str_mv castelo@icmc.usp.br
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