Name
Abstract | ||
|---|---|---|
This paper investigates sparse sampling techniques applied to downsampling and interference detection for multiband radio frequency (RF) signals. To reconstruct a signal from sparse samples is a compressive sensing problem. This paper compares three different reconstruction algorithms: 1) ℓ1 minimization; 2) greedy pursuit; and 3) MUltiple SIgnal Classification (MUSIC). We compare the performance of these algorithms and investigate the robustness to noise effects. Characteristics and limitations of each algorithm are discussed. |
Year | Venue | Field |
|---|---|---|
2011 | European Signal Processing Conference | Matching pursuit,Algorithm design,Pattern recognition,Signal-to-noise ratio,Algorithm,Robustness (computer science),Artificial intelligence,Upsampling,Signal transfer function,Compressed sensing,Signal reconstruction,Mathematics |
DocType | ISSN | Citations |
Conference | 2076-1465 | 0 |
PageRank | References | Authors |
0.34 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao Shen | 1 | 0 | 0.34 |
| Thomas Arildsen | 2 | 28 | 8.21 |
| deepaknath tandur | 3 | 1 | 0.70 |
| Torben Larsen | 4 | 16 | 4.23 |