Computing Bayesian Cramér-Rao bounds


Abstract — An efficient message-passing algorithm for computing the Bayesian Cramér-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. I

Similar works

Full text

oai:CiteSeerX.psu: time updated on 10/22/2014

This paper was published in CiteSeerX.

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.