23 search results - page 4 / 5 » Compressed Sensing: How sharp is the Restricted Isometry Pro... |
SIGPRO
2010
13 years 4 months ago
2010
This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear m...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, s...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
We provide two compressive sensing (CS) recovery algorithms based on iterative hard-thresholding. The algorithms, collectively dubbed as algebraic pursuits (ALPS), exploit the res...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
Recently, the statistical restricted isometry property (STRIP) has been formulated to analyze the performance of deterministic sampling matrices for compressed sensing. In this pa...
FOCM
2011
13 years 22 days ago
2011
The matrix rank minimization problem has applications in many fields such as system identification, optimal control, low-dimensional embedding etc. As this problem is NP-hard in ...