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ICASSP
2011
IEEE
13 years 10 days ago
Bayesian Compressive Sensing for clustered sparse signals
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
Lei Yu, Hong Sun, Jean-Pierre Barbot, Gang Zheng
ICASSP
2011
IEEE
13 years 10 days ago
Compressive sensing meets game theory
We introduce the Multiplicative Update Selector and Estimator (MUSE) algorithm for sparse approximation in underdetermined linear regression problems. Given f = Φα∗ + µ, the ...
Sina Jafarpour, Robert E. Schapire, Volkan Cevher
ICASSP
2011
IEEE
13 years 10 days ago
Short and smooth sampling trajectories for compressed sensing
This paper explores a novel setting for compressed sensing (CS) in which the sampling trajectory length is a critical bottleneck and must be minimized subject to constraints on th...
Rebecca M. Willett
ICASSP
2011
IEEE
13 years 10 days ago
The value of redundant measurement in compressed sensing
The aim of compressed sensing is to recover attributes of sparse signals using very few measurements. Given an overall bit budget for quantization, this paper demonstrates that th...
Victoria Kostina, Marco F. Duarte, Sina Jafarpour,...
CISS
2008
IEEE
14 years 3 months ago
Compressed channel sensing
—Reliable wireless communications often requires accurate knowledge of the underlying multipath channel. This typically involves probing of the channel with a known training wave...
Waheed Uz Zaman Bajwa, Jarvis Haupt, Gil M. Raz, R...