Cited by 10,017Sparse and Compressive Sensing TechniquesMathematical Analysis and Transform MethodsDistributed Sensor Networks and Detection Algorithms

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An Introduction To Compressive Sampling

Candes, E.J., Wakin, M.B.·2008·IEEE Signal Processing Magazine

DOI 10.1109/msp.2007.914731

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Abstract

Conventional approaches to sampling signals or images follow Shannon's theorem: the sampling rate must be at least twice the maximum frequency present in the signal (Nyquist rate). In the field of data conversion, standard analog-to-digital converter (ADC) technology implements the usual quantized Shannon representation - the signal is uniformly sampled at or above the Nyquist rate. This article surveys the theory of compressive sampling, also known as compressed sensing or CS, a novel sensing/sampling paradigm that goes against the common wisdom in data acquisition. CS theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional methods use.

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Authors: Candes, E. J., & Wakin, M. B.
Affiliations: École Polytechnique (FR)
ORCID: Wakin, M.B.
Venue: IEEE Signal Processing Magazine
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2008-03
Volume: 25
Issue: 2
Pages: 21-30
ISSN: 1053-5888 (ISSN-L)
DOI: 10.1109/msp.2007.914731
OpenAlex: W2119667497
Cited by: 10,017
References: 32
Citations by year: 2026: 233 · 2025: 356 · 2024: 359 · 2023: 437 · 2022: 449 · 2021: 561 · 2020: 545 · 2019: 727 · 2018: 818 · 2017: 792 · 2016: 823 · 2015: 899 · 2014: 803 · 2013: 709 · 2012: 614
FWCI: 310.91
Type: journal article
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations: IEEE Signal Processing Magazine (publishedVersion)
HAL (submittedVersion)
Topics: Physical Sciences › Computer Science › Signal Processing › Sparse and Compressive Sensing Techniques
Physical Sciences › Mathematics › Applied Mathematics › Mathematical Analysis and Transform Methods
Physical Sciences › Computer Science › Computer Networks and Communications › Distributed Sensor Networks and Detection Algorithms
Keywords: compressed sensing, Nyquist rate, undersampling, signal reconstruction, image reconstruction, analog-to-digital conversion, data acquisition

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An Introduction To Compressive Sampling

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