Name
Abstract | ||
|---|---|---|
In this paper, we aim to relate different Bayesian Cramer-Rao bounds which appear in the discrete-time nonlinear filtering literature in a single framework. A comparative theoretical analysis of the bounds is provided in order to relate their tightness. The results can be used to provide a lower bound on the mean square error in nonlinear filtering. The findings are illustrated and verified by numerical experiments where the tightness of the bounds are compared. |
Year | Venue | Keywords |
|---|---|---|
2014 | 2014 17TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) | vectors,mean square error,statistical analysis |
Field | DocType | Citations |
Cramér–Rao bound,Upper and lower bounds,Nonlinear filtering,Mean squared error,Artificial intelligence,Discrete time and continuous time,Machine learning,Mathematics,Bayesian probability | Conference | 3 |
PageRank | References | Authors |
0.43 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carsten Fritsche | 1 | 157 | 14.72 |
| Emre Özkan | 2 | 94 | 10.54 |
| Lennart Svensson | 3 | 3 | 0.43 |
| Fredrik Gustafsson | 4 | 2287 | 281.33 |