Approximate Bayesian inference methods for mixture filtering with known model of switching

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU119990" target="_blank" >RIV/00216305:26220/16:PU119990 - isvavai.cz</a>

Result on the web

<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7501157&isnumber=7501055" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7501157&isnumber=7501055</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CarpathianCC.2016.7501157" target="_blank" >10.1109/CarpathianCC.2016.7501157</a>

Result language

angličtina

Original language name

Approximate Bayesian inference methods for mixture filtering with known model of switching

Original language description

Bayesian inference has proven itself to be a practically useful tool for many scientific fields. The exact Bayesian inference is, however, possible in only a narrow class of probabilistic models enjoying the conjugacy principle. It is rather typical that the principle does not hold, and therefore the approximate Bayesian inference methods are taken into account. The present paper compares some of these techniques on a mixture filtering problem. The methods are presented in a generic way, considering that the mixture components are members of the exponential family of probability distributions and that the Markov model of switching between the mixture components is known. A particular instance of the methods is given for a mixture of normal linear state space models, and experiments evaluating the estimation precision and computational time are performed.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LQ1601" target="_blank" >LQ1601: CEITEC 2020</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 17th International Carpathian Control Conference, ICCC 2016

ISBN

978-1-4673-8606-7

ISSN

—

e-ISSN

—

Number of pages

7

Pages from-to

545-551

Publisher name

Institute of Electrical and Electronics Engineers

Place of publication

Tatranska Lomnica

Event location

Tatranská Lomnica

Event date

May 29, 2016

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000389829000102