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Author(s): André Luiz Pilastri
João Manuel R. S. Tavares
Title: Reconstruction Algorithms in Compressive Sensing: An Overview
Issue Date: 2016-02-03
Abstract: 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
Subject: Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
Scientific areas: Ciências da engenharia e tecnologias
Engineering and technology
Source: 11th edition of the Doctoral Symposium in Informatics Engineering (DSIE-16)
Document Type: Artigo em Livro de Atas de Conferência Nacional
Rights: openAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Nacional

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