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ICASSP
2008
IEEE
15 years 10 months ago
Compressive sensing of parameterized shapes in images
Compressive Sensing (CS) uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compressible signals. The Hough t...
Ali Cafer Gurbuz, James H. McClellan, Justin K. Ro...
ICASSP
2011
IEEE
14 years 7 months ago
Iterative hard thresholding for compressed sensing with partially known support
Recent works in modified compressed sensing (CS) show that reconstruction of sparse or compressible signals with partially known support yields better results than traditional CS...
Rafael E. Carrillo, Luisa F. Polania, Kenneth E. B...
121
Voted
CORR
2010
Springer
166views Education» more  CORR 2010»
15 years 3 months ago
The dynamics of message passing on dense graphs, with applications to compressed sensing
`Approximate message passing' algorithms proved to be extremely effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive num...
Mohsen Bayati, Andrea Montanari
111
Voted
DCC
2010
IEEE
15 years 10 months ago
On the Systematic Measurement Matrix for Compressed Sensing in the Presence of Gross Errors
Inspired by syndrome source coding using linear error-correcting codes, we explore a new form of measurement matrix for compressed sensing. The proposed matrix is constructed in t...
Zhi Li, Feng Wu, John Wright
GLOBECOM
2009
IEEE
15 years 10 months ago
Multiple Target Localization Using Compressive Sensing
Abstract— In this paper, a novel multiple target localization approach is proposed by exploiting the compressive sensing theory, which indicates that sparse or compressible signa...
Chen Feng, Shahrokh Valaee, Zhenhui Tan