Bayesian M-T clustering for reduced parameterisation of Markov chains used for non-linear adaptive elements.

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F01%3A16010056" target="_blank" >RIV/67985556:_____/01:16010056 - isvavai.cz</a>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Bayesian M-T clustering for reduced parameterisation of Markov chains used for non-linear adaptive elements.

Original language description

Markov chains are black box models ideal for describing stochastic digitised systems. Although the identification of their parameters can be a relatively easy task to perform, the dimensionality involved become undesirable large. This significant drawback can be overcome by exploiting smoothness of the underlying system. The paper present a novel hybrid off-line algorithm to locate areas which merit detailed model description. It comprises Bayesian parameter estimation and Mean tracking algorithm.

Czech name

—

Czech description

—

Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BC - Theory and management systems

OECD FORD branch

—

Project

<a href="/en/project/GA102%2F99%2F1564" target="_blank" >GA102/99/1564: Research and education centre in adaptive systems - A pilot project</a><br>

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2001

Confidentiality

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

Name of the periodical

Automatica

ISSN

0005-1098

e-ISSN

—

Volume of the periodical

37

Issue of the periodical within the volume

6

Country of publishing house

GB - UNITED KINGDOM

Number of pages

8

Pages from-to

1071-1078

UT code for WoS article

—

EID of the result in the Scopus database

—