Name
Title | ||
|---|---|---|
LMMSE Estimation and Interpolation of Continuous-Time Signals from Discrete-Time Samples Using Factor Graphs |
Abstract | ||
|---|---|---|
The factor graph approach to discrete-time linear Gaussian state space models is well developed. The paper extends this approach to continuous-time linear systems/filters that are driven by white Gaussian noise. By Gaussian message passing, we then obtain MAP/MMSE/LMMSE estimates of the input signal, or of the state, or of the output signal from noisy observations of the output signal. These estimates may be obtained with arbitrary temporal resolution. The proposed input signal estimation does not seem to have appeared in the prior Kalman filtering literature. |
Year | Venue | Field |
|---|---|---|
2013 | CoRR | Factor graph,Mathematical optimization,Linear system,Interpolation,Kalman filter,Gaussian,Discrete time and continuous time,Additive white Gaussian noise,State space,Mathematics |
DocType | Volume | Citations |
Journal | abs/1301.4793 | 3 |
PageRank | References | Authors |
0.53 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lukas Bolliger | 1 | 5 | 0.98 |
| Hans-andrea Loeliger | 2 | 238 | 28.36 |
| Christian Vogel | 3 | 361 | 28.88 |