Name
Abstract | ||
|---|---|---|
We consider a resource-constrained scenario where a compressed sensing- (CS) based sensor has a low number of measurements which are quantized at a low rate followed by transmission or storage. Applying this scenario, we develop a new quantizer design which aims to attain a high-quality reconstruction performance of a sparse source signal based on analysis-by-synthesis framework. Through simulations, we compare the performance of the proposed quantization algorithm vis-a-vis existing quantization methods. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2013.6638778 | 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
Keywords | DocType | Volume |
Quantization, compressed sensing, analysis-by-synthesis, sparsity, mean-square error | Journal | abs/1404.7651 |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
23 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amirpasha Shirazinia | 1 | 62 | 6.90 |
| Saikat Chatterjee | 2 | 24 | 5.32 |
| Mikael Skoglund | 3 | 1397 | 175.71 |