A pragmatic look at some compressive sensing architectures with saturation and quantization

Javier Haboba, Mauro Mangia, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti

Research output: Contribution to journalArticlepeer-review

51 Scopus citations


The paper aims to highlight relative strengths and weaknesses of some of the recently proposed architectures for hardware implementation of analog-to-information converters based on Compressive Sensing. To do so, the most common architectures are analyzed when saturation of some building blocks is taken into account, and when measurements are subject to quantization to produce a digital stream. Furthermore, the signal reconstruction is performed by established and novel algorithms (one based on linear programming and the other based on iterative guessing of the support of the target signal), as well as their specialization to the particular architecture producing the measurements. Performance is assessed both as the probability of correct support reconstruction and as the final reconstruction error. © 2011 IEEE.
Original languageEnglish (US)
Pages (from-to)443-459
Number of pages17
JournalIEEE Journal on Emerging and Selected Topics in Circuits and Systems
Issue number3
StatePublished - Nov 29 2012
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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