Name
Abstract | ||
|---|---|---|
Compressed sensing allows to reconstruct sparse signals sampled at sub-Nyquist rates. However, reconstruction of the original signal requires high computational effort, even for problems of moderate size. Especially for applications with real-time requirements, software realizations are not fast enough. We therefore present generic high-speed FPGA implementations of two fast reconstruction algorithms: orthogonal matching pursuit (OMP) and approximate message passing (AMP). Our implementations also support less sparse signals, which makes them suitable for, e.g., image reconstruction. The two implementations are optimized for highly parallel processing on FPGAs and have similar hardware structures, which allows comparisons in terms of resource usage and performance. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICECS.2012.6463559 | ICECS |
Keywords | Field | DocType |
parallel processing,approximate message passing,omp,sparse signal reconstruction,amp,image reconstruction,compressed sensing,fpga,signal reconstruction,message passing,field programmable gate arrays,compressed sensing reconstruction,orthogonal matching pursuit | Iterative reconstruction,Matching pursuit,Computer science,Parallel processing,Field-programmable gate array,Electronic engineering,Software,Compressed sensing,Signal reconstruction,Message passing | Conference |
ISBN | Citations | PageRank |
978-1-4673-1259-2 | 24 | 1.14 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Bai | 1 | 25 | 3.85 |
| Patrick Maechler | 2 | 99 | 7.06 |
| Michael Muehlberghuber | 3 | 42 | 4.85 |
| Hubert Kaeslin | 4 | 141 | 14.45 |