Name
Abstract | ||
|---|---|---|
Exact reconstruction of finite-rate-of-innovation signals can be achieved by employing customized sampling kernels that satisfy certain frequency-domain properties. We impose compact support in time as an additional constraint. Considering frequency-domain reconstruction, we derive conditions for admissible sampling kernels and corresponding sampling rates. Our constructive kernel design methodolo... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TSP.2017.2733484 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
Kernel,Parameter estimation,Frequency-domain analysis,Splines (mathematics),Time-domain analysis,Laser radar,Optical transmitters | Kernel (linear algebra),Frequency domain,Time domain,Mathematical optimization,Exponential function,Robustness (computer science),Sampling (statistics),Estimation theory,Additive white Gaussian noise,Mathematics | Journal |
Volume | Issue | ISSN |
65 | 22 | 1053-587X |
Citations | PageRank | References |
0 | 0.34 | 40 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Satish Mulleti | 1 | 12 | 2.99 |
| Chandra Sekhar Seelamantula | 2 | 142 | 37.43 |