Name
Abstract | ||
|---|---|---|
This paper considers the problem of detecting the support (sparsity pattern) of a sparse vector from random noisy measurements. Conditional power of a component of the sparse vector is defined as the energy conditioned on the component being nonzero. Analysis of a simplified version of orthogonal matching pursuit (OMP) called sequential OMP (SequOMP) demonstrates the importance of knowledge of the rankings of conditional powers. When the simple SequOMP algorithm is applied to components in nonincreasing order of conditional power, the detrimental effect of dynamic range on thresholding performance is eliminated. Furthermore, under the most favorable conditional powers, the performance of SequOMP approaches maximum likelihood performance at high signal-to-noise ratio. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TSP.2012.2208957 | IEEE Transactions on Signal Processing |
Keywords | DocType | Volume |
iterative methods,maximum likelihood estimation,signal detection,SequOMP algorithm,SequOMP approaches,conditional powers,maximum likelihood performance,orthogonal matching pursuit,random noisy measurements,ranked sparse signal support detection,sequential OMP,signal-to-noise ratio,sparse vector,sparsity pattern,thresholding performance,Compressed sensing,convex optimization,lasso,maximum likelihood estimation,orthogonal matching pursuit,random matrices,sparse Bayesian learning,sparsity,thresholding | Journal | 60 |
Issue | ISSN | Citations |
11 | 1053-587X | 1 |
PageRank | References | Authors |
0.36 | 15 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alyson K. Fletcher | 1 | 552 | 41.10 |
| Sundeep Rangan | 2 | 3101 | 163.90 |
| Vivek K. Goyal | 3 | 2031 | 171.16 |