Name
Abstract | ||
|---|---|---|
This paper considers the problem of sparse signal reconstruction from the timing of its Level Crossings (LC)s. We formulate the sparse Zero Crossing (ZC) reconstruction problem in terms of a single L-blt Compressive Sensing (CS) model. We also extend the Smoothed LO (SLO) sparse reconstruction algorithm to the I-bit CS framework and propose the Binary SLO (BSLO) algorithm for iterative reconstruction of the sparse signal from ZCs in cases where the number of sparse coefficients is not known to the reconstruction algorithm a priori. Similar to the ZC case, we propose a system of simultaneously constrained signed-CS problems to reconstruct a sparse signal from its Level Crossings (LC)s and modify both the Binary Iterative Hard Thresholding (BIHT) and BSLO algorithms to solve this problem. Simulation results demonstrate superior performance of the proposed LC reconstruction techniques in comparison with the literature. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.23919/EUSIPCO.2018.8553367 | 2018 26th European Signal Processing Conference (EUSIPCO) |
Keywords | Field | DocType |
Smoothed LO sparse reconstruction algorithm,I-bit CS framework,Binary SLO algorithm,iterative reconstruction,sparse coefficients,ZC case,signed-CS problems,Level Crossings,LC reconstruction techniques,spectrally sparse signals,sparse signal reconstruction,sparse Zero Crossing reconstruction problem,single L-blt Compressive Sensing model | Iterative reconstruction,Signal processing,Approximation algorithm,Zero crossing,Computer science,Algorithm,Reconstruction algorithm,Thresholding,Signal reconstruction,Compressed sensing | Conference |
ISSN | ISBN | Citations |
2219-5491 | 978-1-5386-3736-4 | 0 |
PageRank | References | Authors |
0.34 | 19 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mahdi Boloursaz Mashhadi | 1 | 23 | 5.13 |
| Hadi. Zayyani | 2 | 96 | 15.51 |
| Saeed Gazor | 3 | 822 | 70.56 |
| Farokh Marvasti | 4 | 573 | 72.71 |