168 search results - page 6 / 34 » Bayesian Compressive Sensing for clustered sparse signals |
CORR
2011
Springer
13 years 2 months ago
2011
Springer
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
ICASSP
2010
IEEE
13 years 6 months ago
2010
IEEE
In this paper, we introduce a novel bayesian compressive sensing (CS) technique for phonetic classification. CS is often used to characterize a signal from a few support training...
TSP
2008
13 years 7 months ago
2008
The data of interest are assumed to be represented as N-dimensional real vectors, and these vectors are compressible in some linear basis B, implying that the signal can be recons...
CORR
2007
Springer
13 years 7 months ago
2007
Springer
This article extends the concept of compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, whic...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
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...