168 search results - page 11 / 34 » Bayesian Compressive Sensing for clustered sparse signals |
CORR
2011
Springer
13 years 2 months ago
2011
Springer
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
ISCAS
2007
IEEE
14 years 1 months ago
2007
IEEE
— The new theory of compressive sensing enables direct analog-to-information conversion of compressible signals at subNyquist acquisition rates. We develop new theory, algorithms...
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
When sampling signals below the Nyquist rate, efficient and accurate reconstruction is nevertheless possible, whenever the sampling system is well behaved and the signal is well ...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measuremen...
ICASSP
2008
IEEE
14 years 2 months ago
2008
IEEE
Compressive Sensing (CS) is an emerging area which uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compres...