Filtering, prediction, and smoothing with gaussian sum representation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F00%3A00056838" target="_blank" >RIV/49777513:23520/00:00056838 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Filtering, prediction, and smoothing with gaussian sum representation

Original language description

The paper dealth with the state estimation problem for discrete time nonlinear nonGaussian stochastic dynamic systems. A description of all random variables of the systém by the Gaussian sums probability density function is considered. This assumption enables to obtain an explicit exact or approximate solution of the three basic types of the state estimation, i.e prediction, filtering and smoothing. Multistep prediction and smoothing for nonlinear and/or nonGaussian systems are newly presented. The stress is laid also on systematic presentation of the new and current results of an application of the Gaussian sums in the nonlinear state estimation problem.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

BC - Theory and management systems

OECD FORD branch

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Project

<a href="/en/project/VS97159" target="_blank" >VS97159: Center for research in the field of cybernetic systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2000

Confidentiality

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

Article name in the collection

Filtering, prediction, and smoothing with gaussian sum representation

ISBN

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ISSN

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e-ISSN

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Number of pages

7

Pages from-to

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Publisher name

IFAC - OMNIPRESS

Place of publication

Santa Barbara

Event location

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Event date

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Type of event by nationality

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UT code for WoS article

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