168 search results - page 13 / 34 » Bayesian Compressive Sensing for clustered sparse signals |
CORR
2010
Springer
13 years 5 months ago
2010
Springer
In this paper, motivated by network inference and tomography applications, we study the problem of compressive sensing for sparse signal vectors over graphs. In particular, we are ...
TSP
2010
13 years 2 months ago
2010
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
TIT
2010
13 years 2 months ago
2010
In [12] the authors proved an asymptotic sampling theorem for sparse signals, showing that n random measurements permit to reconstruct an N-vector having k nonzeros provided n >...
ICASSP
2008
IEEE
14 years 2 months ago
2008
IEEE
The theory of compressed sensing shows that samples in the form of random projections are optimal for recovering sparse signals in high-dimensional spaces (i.e., finding needles ...
ICIP
2010
IEEE
13 years 5 months ago
2010
IEEE
The 2- 1 compressed sensing minimization problem can be solved efficiently by gradient projection. In imaging applications, the signal of interest corresponds to nonnegative pixel...