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» Compressed sensing - a look beyond linear programming
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CORR
2008
Springer
234views Education» more  CORR 2008»
13 years 5 months ago
Bayesian Compressive Sensing via Belief Propagation
Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-N...
Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
JSS
2006
110views more  JSS 2006»
13 years 5 months ago
Beyond source code: The importance of other artifacts in software development (a case study)
Current software systems contain increasingly more elements that have not usually been considered in software engineering research and studies. Source artifacts, understood as the...
Gregorio Robles, Jesús M. González-B...
SIGPRO
2010
135views more  SIGPRO 2010»
13 years 3 months ago
A short note on compressed sensing with partially known signal support
This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear m...
Laurent Jacques
ICASSP
2008
IEEE
13 years 12 months ago
Compressed sensing with sequential observations
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of measurements. The results in the literature have focuse...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
CISS
2008
IEEE
13 years 12 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...