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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

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

Návaznosti

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

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

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

ISBN

978-1-4673-8606-7

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

545-551

Název nakladatele

Institute of Electrical and Electronics Engineers

Místo vydání

Tatranska Lomnica

Místo konání akce

Tatranská Lomnica

Datum konání akce

29. 5. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000389829000102