ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly spa...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
NIPS
2008
13 years 6 months ago
2008
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
CIMAGING
2008
13 years 6 months ago
2008
This paper seeks to bridge the two major algorithmic approaches to sparse signal recovery from an incomplete set of linear measurements
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
The theory of compressive sensing has shown that sparse signals can be reconstructed exactly from many fewer measurements than traditionally believed necessary. In [1], it was sho...
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
The batch least-absolute shrinkage and selection operator (Lasso) has well-documented merits for estimating sparse signals of interest emerging in various applications, where obse...
ICIP
2008
IEEE
14 years 6 months ago
2008
IEEE
We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incohe...