25 search results - page 3 / 5 » Bayesian compressive sensing and projection optimization |
ICASSP
2008
IEEE
14 years 1 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...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
A parallel structure to do spectrum sensing in Cognitive Radio (CR) at sub-Nyquist rate is proposed. The structure is based on Compressed Sensing (CS) that exploits the sparsity o...
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
TIT
2010
13 years 2 months ago
2010
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...