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CISS
2010
IEEE
12 years 8 months ago
Compressive sampling for streaming signals with sparse frequency content
Abstract—Compressive sampling (CS) has emerged as significant signal processing framework to acquire and reconstruct sparse signals at rates significantly below the Nyquist rate...
Petros Boufounos, M. Salman Asif
ICASSP
2011
IEEE
12 years 8 months 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
CORR
2008
Springer
161views Education» more  CORR 2008»
13 years 3 months ago
Compressed Sensing of Analog Signals
Abstract--A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on ...
Yonina C. Eldar
CORR
2011
Springer
155views Education» more  CORR 2011»
12 years 11 months ago
Reconciling Compressive Sampling Systems for Spectrally-sparse Continuous-time Signals
The Random Demodulator (RD) and the Modulated Wideband Converter (MWC) are two recently proposed compressed sensing (CS) techniques for the acquisition of continuous-time spectral...
Michael A. Lexa, Mike E. Davies, John S. Thompson
CORR
2010
Springer
172views Education» more  CORR 2010»
13 years 4 months ago
The MUSIC Algorithm for Sparse Objects: A Compressed Sensing Analysis
The MUSIC algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to a...
Albert Fannjiang