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CORR
2011
Springer
214views Education» more  CORR 2011»
12 years 8 months ago
K-Median Clustering, Model-Based Compressive Sensing, and Sparse Recovery for Earth Mover Distance
We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m × n matrices A such that for any x, given A...
Piotr Indyk, Eric Price
CORR
2008
Springer
178views Education» more  CORR 2008»
13 years 4 months ago
Model-Based Compressive Sensing
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals that can be well approximated by just K N elements from a...
Richard G. Baraniuk, Volkan Cevher, Marco F. Duart...
CORR
2008
Springer
144views Education» more  CORR 2008»
13 years 4 months ago
Iterative Hard Thresholding for Compressed Sensing
Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present ...
Thomas Blumensath, Mike E. Davies
ICIP
2009
IEEE
14 years 5 months ago
On The Empirical Rate-distortion Performance Of Compressive Sensing
Compressive Sensing (CS) is a new paradigm in signal acquisition and compression. In compressive sensing, a compressible signal is acquired using much less measurements than the o...
ICASSP
2011
IEEE
12 years 8 months ago
Ambiguity functions of compressively sensed and processed radar waveforms
Compressive sensing and processing delivers high resolution data using reduced sampling rates and computational effort compared to Nyquist sensing and processing. Compressive proc...
Ioannis Kyriakides