Name
Abstract | ||
|---|---|---|
In this paper we develop a comprehensive framework for the study of decentralized estimation problems. This approach imbeds a decentralized estimation problem into an equivalent scattering problem, and makes use of the super-position principle to relate local and centralized estimates. Some decentralized filtering and smoothing algorithms are obtained for a simple estimation structure consisting of a central processor and of two local processors. The case when the local processors exchange some information is considered, as well as the case when the local state-space models differ from the central model. |
Year | DOI | Venue |
|---|---|---|
1983 | 10.1016/0005-1098(83)90051-1 | Automatica |
Keywords | Field | DocType |
Filtering,smoothing,state-estimation,Kalman filters,large-scale systems,hierarchical systems | Least squares,Flow network,Signal processing,Mathematical optimization,Computer science,Control theory,Filter (signal processing),Kalman filter,Smoothing,Scattering,Hierarchy | Journal |
Volume | Issue | ISSN |
19 | 4 | 0005-1098 |
Citations | PageRank | References |
11 | 4.87 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bernard C. Levy | 1 | 245 | 31.17 |
| David A. Castañón | 2 | 324 | 60.41 |
| George C. Verghese | 3 | 208 | 26.26 |
| Alan S. Willsky | 4 | 7466 | 847.01 |