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Bayesian estimation of unknown parameters over networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00462059" target="_blank" >RIV/67985556:_____/16:00462059 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/EUSIPCO.2016.7760500" target="_blank" >http://dx.doi.org/10.1109/EUSIPCO.2016.7760500</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/EUSIPCO.2016.7760500" target="_blank" >10.1109/EUSIPCO.2016.7760500</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Bayesian estimation of unknown parameters over networks

  • Original language description

    We address the problem of sequential parameter estimation over networks using the Bayesian methodology. Each node sequentially acquires independent observations, where all the observations in the network contain signal(s) with unknown parameters. The nodes aim at obtaining accurate estimates of the unknown parameters and to that end, they collaborate with their neighbors. They communicate to the neighbors their latest posterior distributions of the unknown parameters. The nodes fuse the received information by using mixtures with weights proportional to the predictive distributions obtained from the respective node posteriors. Then they update the fused posterior using the next acquired observation, and the process repeats. We demonstrate the performance of the proposed approach with computer simulations and confirm its validity

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GP14-06678P" target="_blank" >GP14-06678P: Distributed dynamic estimation in diffusion networks</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proc. 2016 24th European Signal Processing Conference (EUSIPCO)

  • ISBN

    978-0-9928-6266-4

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    1508-1512

  • Publisher name

    EUSIPCO

  • Place of publication

    Budapest

  • Event location

    Budapest

  • Event date

    Aug 29, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000391891900289