DocumentCode
2266817
Title
Computing Bayesian Cramer-Rao bounds
Author
Dauwels, Justin
Author_Institution
Dept. of Inf. Technol. & Electr. Eng., ETH, Zurich
fYear
2005
fDate
4-9 Sept. 2005
Firstpage
425
Lastpage
429
Abstract
An efficient message-passing algorithm for computing the Bayesian Cramer-Rao bound (BCRB) for general estimation problems is presented. The BCRB is a lower bound on the mean squared estimation error. The algorithm operates on a cycle-free factor graph of the system at hand. It can be applied to estimation in (1) general state-space models; (2) coupled state-space models and other systems that are most naturally represented by cyclic factor graphs; (3) coded systems
Keywords
Bayes methods; codes; graph theory; least mean squares methods; Bayesian Cramer-Rao bounds; coded systems; coupled state-space models; cycle-free factor graph; general estimation problems; general state-space models; mean squared estimation error; message-passing algorithm; Bayesian methods; Channel estimation; Estimation error; Filtering; Frequency estimation; Information technology; Maximum a posteriori estimation; Maximum likelihood estimation; Smoothing methods; State estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2005. ISIT 2005. Proceedings. International Symposium on
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-9151-9
Type
conf
DOI
10.1109/ISIT.2005.1523369
Filename
1523369
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