Name
Abstract | ||
|---|---|---|
The effect of off-grid atoms has become the prominent problem in application of the Compressed Sensing (CS) techniques to the cases where there is an underlying continuous parametrization. In this work, we develop a generalizing CS framework which shows that sampling to a finite grid is not necessary toward compressive estimation. We propose an alternative procedure over infinite dictionaries, which we show to be theoretically consistent in many cases of interest and then propose a robust implementation. We illustrate the general properties of our technique in some difficult practical instances of frequency estimation. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2014.6854228 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
compressed sensing,frequency estimation,signal sampling,CS framework,compressive estimation,frequency estimation,gridless compressive sensing,infinite dictionaries,off-grid atoms | Mathematical optimization,Parametrization,Computer science,Generalization,Sampling (statistics),Compressed sensing,Grid | Conference |
ISSN | Citations | PageRank |
1520-6149 | 3 | 0.41 |
References | Authors | |
6 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ashkan Panahi | 1 | 93 | 13.97 |
| M. Viberg | 2 | 917 | 188.13 |