Recent Results on Bayesian Cramer-Rao Bounds for Jump Markov Systems
Paper i proceeding, 2016

In this paper, recent results on the evaluation of the Bayesian Cramer-Rao bound for jump Markov systems are presented. In particular, previous work is extended to jump Markov systems where the discrete mode variable enters into both the process and measurement equation, as well as where it enters exclusively into the measurement equation. Recursive approximations are derived with finite memory requirements as well as algorithms for checking the validity of these approximations are established. The tightness of the bound and the validity of its approximation is investigated on a couple of examples.

Computational modeling

Bayes methods

Mathematical model

Markov processes

State

Cramer-Rao bounds

Engineering

Filter

Computer Science

Approximation algorithms

Monte Carlo methods

Författare

C. Fritsche

U. Orguner

Lennart Svensson

Chalmers, Signaler och system

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

F. Gustafsson

2016 19th International Conference on Information Fusion (Fusion)

512-520

Drivkrafter

Hållbar utveckling

Ämneskategorier

Elektroteknik och elektronik

Signalbehandling

Styrkeområden

Materialvetenskap

ISBN

978-0-9964-5274-8

Mer information

Skapat

2017-10-08