Reconstruction Algorithms in Compressive Sensing: An Overview

Detalhes bibliográficos
Autor(a) principal: André Luiz Pilastri
Data de Publicação: 2016
Outros Autores: João Manuel R. S. Tavares
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://repositorio-aberto.up.pt/handle/10216/85157
Resumo: The theory Compressive Sensing (CS) has provided a newacquisition strategy and recovery with good in the image processing area.This theory guarantees to recover a signal with high probability from areduced sampling rate below the Nyquist-Shannon limit. The problem ofrecovering the original signal from the samples consists in solving an optimizationproblem. This article presents an overview of reconstructionalgorithms for sparse signal recovery in CS, these algorithms may bebroadly divided into six types. We have provided a comprehensive surveyof the numerous reconstruction algorithms in CS aiming to achievecomputational efficiency
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spelling Reconstruction Algorithms in Compressive Sensing: An OverviewCiências Tecnológicas, Ciências da engenharia e tecnologiasTechnological sciences, Engineering and technologyThe theory Compressive Sensing (CS) has provided a newacquisition strategy and recovery with good in the image processing area.This theory guarantees to recover a signal with high probability from areduced sampling rate below the Nyquist-Shannon limit. The problem ofrecovering the original signal from the samples consists in solving an optimizationproblem. This article presents an overview of reconstructionalgorithms for sparse signal recovery in CS, these algorithms may bebroadly divided into six types. We have provided a comprehensive surveyof the numerous reconstruction algorithms in CS aiming to achievecomputational efficiency2016-02-032016-02-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://repositorio-aberto.up.pt/handle/10216/85157engAndré Luiz PilastriJoão Manuel R. S. Tavaresinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:48:25Zoai:repositorio-aberto.up.pt:10216/85157Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:08:57.360529Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Reconstruction Algorithms in Compressive Sensing: An Overview
title Reconstruction Algorithms in Compressive Sensing: An Overview
spellingShingle Reconstruction Algorithms in Compressive Sensing: An Overview
André Luiz Pilastri
Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
title_short Reconstruction Algorithms in Compressive Sensing: An Overview
title_full Reconstruction Algorithms in Compressive Sensing: An Overview
title_fullStr Reconstruction Algorithms in Compressive Sensing: An Overview
title_full_unstemmed Reconstruction Algorithms in Compressive Sensing: An Overview
title_sort Reconstruction Algorithms in Compressive Sensing: An Overview
author André Luiz Pilastri
author_facet André Luiz Pilastri
João Manuel R. S. Tavares
author_role author
author2 João Manuel R. S. Tavares
author2_role author
dc.contributor.author.fl_str_mv André Luiz Pilastri
João Manuel R. S. Tavares
dc.subject.por.fl_str_mv Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
topic Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
description The theory Compressive Sensing (CS) has provided a newacquisition strategy and recovery with good in the image processing area.This theory guarantees to recover a signal with high probability from areduced sampling rate below the Nyquist-Shannon limit. The problem ofrecovering the original signal from the samples consists in solving an optimizationproblem. This article presents an overview of reconstructionalgorithms for sparse signal recovery in CS, these algorithms may bebroadly divided into six types. We have provided a comprehensive surveyof the numerous reconstruction algorithms in CS aiming to achievecomputational efficiency
publishDate 2016
dc.date.none.fl_str_mv 2016-02-03
2016-02-03T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
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status_str publishedVersion
dc.identifier.uri.fl_str_mv https://repositorio-aberto.up.pt/handle/10216/85157
url https://repositorio-aberto.up.pt/handle/10216/85157
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.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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