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CDC
2010
IEEE
140views Control Systems» more  CDC 2010»
14 years 4 months ago
On the observability of linear systems from random, compressive measurements
Abstract-- Recovering or estimating the initial state of a highdimensional system can require a potentially large number of measurements. In this paper, we explain how this burden ...
Michael B. Wakin, Borhan Molazem Sanandaji, Tyrone...
INFOCOM
2010
IEEE
14 years 8 months ago
Compressive Oversampling for Robust Data Transmission in Sensor Networks
—Data loss in wireless sensing applications is inevitable and while there have been many attempts at coping with this issue, recent developments in the area of Compressive Sensin...
Zainul Charbiwala, Supriyo Chakraborty, Sadaf Zahe...
INTERSPEECH
2010
14 years 4 months ago
Artificial and online acquired noise dictionaries for noise robust ASR
Recent research has shown that speech can be sparsely represented using a dictionary of speech segments spanning multiple frames, exemplars, and that such a sparse representation ...
Jort F. Gemmeke, Tuomas Virtanen
CORR
2010
Springer
93views Education» more  CORR 2010»
14 years 9 months ago
Rank Awareness in Joint Sparse Recovery
In this paper we revisit the sparse multiple measurement vector (MMV) problem, where the aim is to recover a set of jointly sparse multichannel vectors from incomplete measurement...
Mike E. Davies, Yonina C. Eldar
CORR
2008
Springer
98views Education» more  CORR 2008»
14 years 9 months ago
Sparse Recovery by Non-convex Optimization -- Instance Optimality
In this note, we address the theoretical properties of p, a class of compressed sensing decoders that rely on p minimization with p (0, 1) to recover estimates of sparse and compr...
Rayan Saab, Özgür Yilmaz