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JDCTA
2010
188views more  JDCTA 2010»
12 years 11 months ago
Compressive Sensing Signal Detection Algorithm Based on Location Information of Sparse Coefficients
Without reconstructing the signal themselves, signal detection could be solved by detection algorithm, which directly processes sampling value obtained from compressive sensing si...
Bing Liu, Ping Fu, Shengwei Meng, Lunping Guo
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...
ICASSP
2008
IEEE
13 years 11 months ago
Subspace compressive detection for sparse signals
The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
Zhongmin Wang, Gonzalo R. Arce, Brian M. Sadler
CORR
2008
Springer
234views Education» more  CORR 2008»
13 years 4 months ago
Bayesian Compressive Sensing via Belief Propagation
Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-N...
Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
ISCAS
2007
IEEE
126views Hardware» more  ISCAS 2007»
13 years 10 months ago
Theory and Implementation of an Analog-to-Information Converter using Random Demodulation
— The new theory of compressive sensing enables direct analog-to-information conversion of compressible signals at subNyquist acquisition rates. We develop new theory, algorithms...
Jason N. Laska, Sami Kirolos, Marco F. Duarte, Tam...