Title :
Computing Bayesian Cramer-Rao bounds
Author_Institution :
Dept. of Inf. Technol. & Electr. Eng., ETH, Zurich
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;
Conference_Titel :
Information Theory, 2005. ISIT 2005. Proceedings. International Symposium on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-9151-9
DOI :
10.1109/ISIT.2005.1523369
