Sequential Estimation of Mixtures in Diffusion Networks

Result code in IS VaVaI

RIV/67985556:_____/15:00431479 - isvavai.cz

Result on the web

http://dx.doi.org/10.1109/LSP.2014.2353652

DOI - Digital Object Identifier

10.1109/LSP.2014.2353652

Result language

angličtina

Original language name

Sequential Estimation of Mixtures in Diffusion Networks

Original language description

The letter studies the problem of sequential estimation of mixtures in diffusion networks whose nodes communicate only with their adjacent neighbors. The adopted quasi-Bayesian approach yields a probabilistically consistent and computationally non-intensive and fast method, applicable to a wide class of mixture models with unknown component parameters and weights. Moreover, if conjugate priors are used for inferring the component parameters, the solution attains a closed analytic form.

Czech name

—

Czech description

—

Type

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

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

—

Project

GP14-06678P: Distributed dynamic estimation in diffusion networks

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2015

Confidentiality

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

Name of the periodical

IEEE Signal Processing Letters

ISSN

1070-9908

e-ISSN

—

Volume of the periodical

22

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

5

Pages from-to

197-201

UT code for WoS article

000342159700009

EID of the result in the Scopus database

2-s2.0-84907191888