Name
Abstract | ||
|---|---|---|
This article introduces the Rayleigh autoregressive moving average (RARMA) model, which is useful to interpret multiple different sets of remotely sensed data, from wind measurements to multitemporal synthetic aperture radar (SAR) sequences. The RARMA model is indeed suitable for continuous, asymmetric, and nonnegative signals observed over time. It describes the mean of Rayleigh-distributed discr... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TGRS.2020.2971345 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Autoregressive processes,Synthetic aperture radar,Remote sensing,Data models,Wind speed,Feature extraction,Time series analysis | Journal | 58 |
Issue | ISSN | Citations |
7 | 0196-2892 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fábio M. Bayer | 1 | 126 | 12.89 |
| Debora M. Bayer | 2 | 0 | 0.34 |
| Andrea Marinoni | 3 | 48 | 13.37 |
| Paolo Gamba | 4 | 682 | 92.97 |