168 search results - page 9 / 34 » Bayesian Compressive Sensing for clustered sparse signals |
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Due to multipath delay spread and relatively high sampling rate in OFDM systems, the channel estimation is formulated as a sparse recovery problem, where a hybrid compressed sensi...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
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...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Compressed sensing is a novel technique where one can recover sparse signals from the undersampled measurements. In this paper, a K × N measurement matrix for compressed sensing ...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
In recent work, Kalman Filtered Compressed Sensing (KF-CS) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measure...