Name
Abstract | ||
|---|---|---|
The ensemble Kalman filter (EnKF) is a Monte Carlo-based implementation of the Kalman filter (KF) for extremely high-dimensional, possibly nonlinear, and non-Gaussian state estimation problems. Its ability to handle state dimensions in the order of millions has made the EnKF a popular algorithm in different geoscientific disciplines. Despite a similarly vital need for scalable algorithms in signal processing, e.g., to make sense of the ever increasing amount of sensor data, the EnKF is hardly discussed in our field. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1186/s13634-017-0492-x | EURASIP J. Adv. Sig. Proc. |
DocType | Volume | Issue |
Journal | abs/1702.08061 | 1 |
ISSN | Citations | PageRank |
EURASIP J. Adv. Signal Process. (2017) 2017: 56 | 4 | 0.57 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Roth | 1 | 4 | 0.57 |
| Gustaf Hendeby | 2 | 216 | 21.37 |
| Carsten Fritsche | 3 | 157 | 14.72 |
| Fredrik Gustafsson | 4 | 2287 | 281.33 |