Sequentially designed compressed sensing

J. Haupt; R.G. Baraniuk; R.M. Castro; R. Nowak

doi:10.1109/SSP.2012.6319715

Sequentially designed compressed sensing

J. Haupt, R.G. Baraniuk, R.M. Castro, R. Nowak

Statistics - Stieltjes

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

40 Citations (Scopus)

Abstract

A sequential adaptive compressed sensing procedure for signal support recovery is proposed and analyzed. The procedure is based on the principle of distilled sensing, and makes used of sparse sensing matrices to perform sketching observations able to quickly identify irrelevant signal components. It is shown that adaptive compressed sensing enables recovery of weaker sparse signals than those that can be recovered using traditional non-adaptive compressed sensing approaches.

Original language	English
Title of host publication	Proceedings of the 2012 IEEE Statistical Signal Processing Workshop (Ann Arbor MI, USA, August 5-8, 2012)
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	401-404
ISBN (Print)	978-1-4673-0183-1
DOIs	https://doi.org/10.1109/SSP.2012.6319715
Publication status	Published - 2012
Event	conference; 2012 IEEE Statistical Signal Processing Workshop; 2012-08-05; 2012-08-08 - Duration: 5 Aug 2012 → 8 Aug 2012

Conference

Conference	conference; 2012 IEEE Statistical Signal Processing Workshop; 2012-08-05; 2012-08-08
Period	5/08/12 → 8/08/12
Other	2012 IEEE Statistical Signal Processing Workshop

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10.1109/SSP.2012.6319715

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title = "Sequentially designed compressed sensing",

abstract = "A sequential adaptive compressed sensing procedure for signal support recovery is proposed and analyzed. The procedure is based on the principle of distilled sensing, and makes used of sparse sensing matrices to perform sketching observations able to quickly identify irrelevant signal components. It is shown that adaptive compressed sensing enables recovery of weaker sparse signals than those that can be recovered using traditional non-adaptive compressed sensing approaches.",

author = "J. Haupt and R.G. Baraniuk and R.M. Castro and R. Nowak",

year = "2012",

doi = "10.1109/SSP.2012.6319715",

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booktitle = "Proceedings of the 2012 IEEE Statistical Signal Processing Workshop (Ann Arbor MI, USA, August 5-8, 2012)",

publisher = "Institute of Electrical and Electronics Engineers",

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note = "conference; 2012 IEEE Statistical Signal Processing Workshop; 2012-08-05; 2012-08-08 ; Conference date: 05-08-2012 Through 08-08-2012",

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Haupt, J, Baraniuk, RG, Castro, RM & Nowak, R 2012, Sequentially designed compressed sensing. in Proceedings of the 2012 IEEE Statistical Signal Processing Workshop (Ann Arbor MI, USA, August 5-8, 2012). Institute of Electrical and Electronics Engineers, Piscataway, pp. 401-404, conference; 2012 IEEE Statistical Signal Processing Workshop; 2012-08-05; 2012-08-08, 5/08/12. https://doi.org/10.1109/SSP.2012.6319715

Sequentially designed compressed sensing. / Haupt, J.; Baraniuk, R.G.; Castro, R.M.; Nowak, R.

Proceedings of the 2012 IEEE Statistical Signal Processing Workshop (Ann Arbor MI, USA, August 5-8, 2012). Piscataway : Institute of Electrical and Electronics Engineers, 2012. p. 401-404.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Sequentially designed compressed sensing

AU - Haupt, J.

AU - Baraniuk, R.G.

AU - Castro, R.M.

AU - Nowak, R.

PY - 2012

Y1 - 2012

N2 - A sequential adaptive compressed sensing procedure for signal support recovery is proposed and analyzed. The procedure is based on the principle of distilled sensing, and makes used of sparse sensing matrices to perform sketching observations able to quickly identify irrelevant signal components. It is shown that adaptive compressed sensing enables recovery of weaker sparse signals than those that can be recovered using traditional non-adaptive compressed sensing approaches.

AB - A sequential adaptive compressed sensing procedure for signal support recovery is proposed and analyzed. The procedure is based on the principle of distilled sensing, and makes used of sparse sensing matrices to perform sketching observations able to quickly identify irrelevant signal components. It is shown that adaptive compressed sensing enables recovery of weaker sparse signals than those that can be recovered using traditional non-adaptive compressed sensing approaches.

U2 - 10.1109/SSP.2012.6319715

DO - 10.1109/SSP.2012.6319715

M3 - Conference contribution

SN - 978-1-4673-0183-1

SP - 401

EP - 404

BT - Proceedings of the 2012 IEEE Statistical Signal Processing Workshop (Ann Arbor MI, USA, August 5-8, 2012)

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - conference; 2012 IEEE Statistical Signal Processing Workshop; 2012-08-05; 2012-08-08

Y2 - 5 August 2012 through 8 August 2012

ER -

Sequentially designed compressed sensing

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