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STOC
2007
ACM
106views Algorithms» more  STOC 2007»
14 years 8 months ago
One sketch for all: fast algorithms for compressed sensing
Compressed Sensing is a new paradigm for acquiring the compressible signals that arise in many applications. These signals can be approximated using an amount of information much ...
Anna C. Gilbert, Martin J. Strauss, Joel A. Tropp,...
ICASSP
2011
IEEE
13 years 6 days 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...
ICIP
2009
IEEE
14 years 9 months ago
Dequantizing Compressed Sensing With Non-gaussian Constraints
In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...
ICASSP
2008
IEEE
14 years 2 months ago
Mixed-signal parallel compressed sensing and reception for cognitive radio
A parallel structure to do spectrum sensing in Cognitive Radio (CR) at sub-Nyquist rate is proposed. The structure is based on Compressed Sensing (CS) that exploits the sparsity o...
Zhuizhuan Yu, Sebastian Hoyos, Brian M. Sadler
ICASSP
2009
IEEE
14 years 3 months ago
Real-time dynamic MR image reconstruction using Kalman Filtered Compressed Sensing
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...
Chenlu Qiu, Wei Lu, Namrata Vaswani