Sequentially designed compressed sensing

Jarvis Haupt; Richard Baraniuk; Rui Castro; Robert Nowak

doi:10.1109/SSP.2012.6319715

Sequentially designed compressed sensing

Jarvis Haupt, Richard Baraniuk, Rui Castro, Robert Nowak

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

41 Scopus citations

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 (US)
Title of host publication	2012 IEEE Statistical Signal Processing Workshop, SSP 2012
Pages	401-404
Number of pages	4
DOIs	https://doi.org/10.1109/SSP.2012.6319715
State	Published - Nov 6 2012
Event	2012 IEEE Statistical Signal Processing Workshop, SSP 2012 - Ann Arbor, MI, United States Duration: Aug 5 2012 → Aug 8 2012

Other

Other	2012 IEEE Statistical Signal Processing Workshop, SSP 2012
Country/Territory	United States
City	Ann Arbor, MI
Period	8/5/12 → 8/8/12

Keywords

Adaptive sensing
compressed sensing
support recovery

ASJC Scopus subject areas

Signal Processing

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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.",

keywords = "Adaptive sensing, compressed sensing, support recovery",

author = "Jarvis Haupt and Richard Baraniuk and Rui Castro and Robert Nowak",

year = "2012",

month = nov,

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doi = "10.1109/SSP.2012.6319715",

language = "English (US)",

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AU - Haupt, Jarvis

AU - Baraniuk, Richard

AU - Castro, Rui

AU - Nowak, Robert

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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.

KW - Adaptive sensing

KW - compressed sensing

KW - support recovery

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U2 - 10.1109/SSP.2012.6319715

DO - 10.1109/SSP.2012.6319715

M3 - Conference contribution

AN - SCOPUS:84868218048

SN - 9781467301831

SP - 401

EP - 404

BT - 2012 IEEE Statistical Signal Processing Workshop, SSP 2012

T2 - 2012 IEEE Statistical Signal Processing Workshop, SSP 2012

Y2 - 5 August 2012 through 8 August 2012

ER -

Sequentially designed compressed sensing

Abstract

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Keywords

ASJC Scopus subject areas

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