Name
Abstract | ||
|---|---|---|
Finite rate of innovation (FRI) is a recent framework for sampling and reconstruction of a large class of parametric signals that are characterized by finite number of innovations (parameters) per unit interval. In the absence of noise, exact recovery of FRI signals has been demonstrated. In the noisy scenario, there exist techniques to deal with non-ideal measurements. Yet, the accuracy and resil... |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TSP.2015.2461513 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
Technological innovation,Kernel,Estimation,Noise,Reconstruction algorithms,Biological system modeling,Computational modeling | Cramér–Rao bound,Kernel (linear algebra),Mathematical optimization,Matrix pencil,Upper and lower bounds,Computer science,Unit interval,Parametric statistics,Sampling (statistics),Signal reconstruction | Journal |
Volume | Issue | ISSN |
63 | 22 | 1053-587X |
Citations | PageRank | References |
4 | 0.46 | 24 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zafer Dogan | 1 | 12 | 1.93 |
| Christopher Gilliam | 2 | 26 | 5.97 |
| T Blu | 3 | 2574 | 259.70 |
| Dimitri Van De Ville | 4 | 1656 | 118.48 |