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    Random Acquisition in Compressive Sensing: A Comprehensive Overview

    Autor: 
    Khosravy, Mahdi
    ;
    Cabral, Thales Wulfert
    ;
    Luiz, Max Mateus
    ;
    Gupta, Neeraj
    ;
    González-Crespo, Rubén (1)
    Fecha: 
    2021
    Palabra clave: 
    compressive sensing; random acquisition; random demodulation; signal sampling; Emerging; Scopus
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/12306
    DOI: 
    https://doi.org/10.4018/IJACI.2021070107
    Dirección web: 
    https://www.igi-global.com/gateway/article/279589
    Resumen:
    Compressive sensing has the ability of reconstruction of signal/image from the compressive measurements which are sensed with a much lower number of samples than a minimum requirement by Nyquist sampling theorem. The random acquisition is widely suggested and used for compressive sensing. In the random acquisition, the randomness of the sparsity structure has been deployed for compressive sampling of the signal/image. The article goes through all the literature up to date and collects the main methods, and simply described the way each of them randomly applies the compressive sensing. This article is a comprehensive review of random acquisition techniques in compressive sensing. Theses techniques have reviews under the main categories of (1) random demodulator, (2) random convolution, (3) modulated wideband converter model, (4) compressive multiplexer diagram, (5) random equivalent sampling, (6) random modulation pre-integration, (7) quadrature analog-to-information converter, (8) randomly triggered modulated-wideband compressive sensing (RT-MWCS).
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