Compressive sampling for signal classification

Jarvis Haupt; Rui Castro; Robert Nowak; Gerald Fudge; Alex Yeh

doi:10.1109/ACSSC.2006.354994

Compressive sampling for signal classification

Jarvis Haupt, Rui Castro, Robert Nowak, Gerald Fudge, Alex Yeh

Electrical and Computer Engineering

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

103 Scopus citations

Abstract

Compressive Sampling (CS), also called Compressed Sensing, entails making observations of an unknown signal by projecting it onto random vectors. Recent theoretical results show that if the signal is sparse (or nearly sparse) in some basis, then with high probability such observations essentially encode the salient information in the signal. Further, the signal can be reconstructed from these "random projections," even when the number of observations is far less than the ambient signal dimension. The provable success of CS for signal reconstruction motivates the study of its potential in other applications. This paper investigates the utility of CS projection observations for signal classification (more specifically, mary hypothesis testing). Theoretical error bounds are derived and verified with several simulations.

Original language	English (US)
Title of host publication	Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages	1430-1434
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2006.354994
State	Published - Dec 1 2006
Event	40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States Duration: Oct 29 2006 → Nov 1 2006

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)	1058-6393

Other

Other	40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
Country/Territory	United States
City	Pacific Grove, CA
Period	10/29/06 → 11/1/06

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Compressive sampling for signal classification. / Haupt, Jarvis; Castro, Rui; Nowak, Robert et al.
Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06. 2006. p. 1430-1434 4176804 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

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

Haupt, J, Castro, R, Nowak, R, Fudge, G & Yeh, A 2006, Compressive sampling for signal classification. in Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06., 4176804, Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 1430-1434, 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06, Pacific Grove, CA, United States, 10/29/06. https://doi.org/10.1109/ACSSC.2006.354994

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AU - Nowak, Robert

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Compressive sampling for signal classification

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