Name
Title | ||
|---|---|---|
Performance comparison of reconstruction algorithms in discrete blind multi-coset sampling |
Abstract | ||
|---|---|---|
This paper investigates the performance of different reconstruction algorithms in discrete blind multi-coset sampling. Multi-coset scheme is a promising compressed sensing architecture that can replace traditional Nyquist-rate sampling in the applications with multi-band frequency sparse signals. The performance of the existing compressed sensing reconstruction algorithms have not been investigated yet for the discrete multi-coset sampling. We compare the following algorithms - orthogonal matching pursuit, multiple signal classification, subspace-augmented multiple signal classification, focal under-determined system solver and basis pursuit denoising. The comparison is performed via numerical simulations for different sampling conditions. According to the simulations, focal under-determined system solver outperforms all other algorithms for signals with low signal-to-noise ratio. In other cases, the multiple signal classification algorithm is more beneficial. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ISSPIT.2012.6621277 | Signal Processing and Information Technology |
Keywords | DocType | ISSN |
compressed sensing,numerical analysis,pattern matching,sampling methods,signal classification,signal denoising,signal reconstruction,nyquist-rate sampling,basis pursuit denoising algorithm,compressed sensing architecture,compressed sensing reconstruction algorithms,discrete blind multicoset sampling,focal under-determined system solver algorithm,multiband frequency sparse signal,multiple signal classification algorithm,numerical simulations,orthogonal matching pursuit algorithm,signal-to-noise ratio,subspace-augmented multiple signal classification algorithm,multi-band signals,multi-coset sampling,multiple-measurement vectors | Conference | 2162-7843 |
ISBN | Citations | PageRank |
978-1-4673-5604-6 | 2 | 0.37 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruben Grigoryan | 1 | 2 | 0.37 |
| Thomas Arildsen | 2 | 28 | 8.21 |
| Deepaknath Tandur | 3 | 2 | 0.37 |
| Torben Larsen | 4 | 16 | 4.23 |