Sparse signal recovery and acquisition with graphical models

Volkan Cevher; Piotr Indyk; Lawrence Carin; Richard Baraniuk

doi:10.1109/MSP.2010.938029

Sparse signal recovery and acquisition with graphical models

Volkan Cevher, Piotr Indyk, Lawrence Carin, Richard Baraniuk

Research output: Contribution to journal › Article › peer-review

53 Scopus citations

Abstract

Many applications in digital signal processing, machine learning, and communications feature a linear regression problem in which unknown data points, hidden variables, or code words are projected into a lower dimensional space via © 2006 IEEE.

Original language	English (US)
Pages (from-to)	92-103
Number of pages	12
Journal	IEEE Signal Processing Magazine
Volume	27
Issue number	6
DOIs	https://doi.org/10.1109/MSP.2010.938029
State	Published - Jan 1 2010
Externally published	Yes

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Generated from Scopus record by KAUST IRTS on 2021-02-09

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10.1109/MSP.2010.938029

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abstract = "Many applications in digital signal processing, machine learning, and communications feature a linear regression problem in which unknown data points, hidden variables, or code words are projected into a lower dimensional space via {\textcopyright} 2006 IEEE.",

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AU - Carin, Lawrence

AU - Baraniuk, Richard

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JO - IEEE Signal Processing Magazine

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Sparse signal recovery and acquisition with graphical models

Abstract

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