Change point detection algorithms for complex physical dynamical systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F12%3A00199587" target="_blank" >RIV/68407700:21340/12:00199587 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Change point detection algorithms for complex physical dynamical systems

Popis výsledku v původním jazyce

The target of this contribution is to present an integrated overview of algorithms which could be used for change point detection of any physical dynamical system, e.g. in acoustic system or for the particle detection in accelerated physics. Furthermorewe want to show a possible improvement of the localization of the source of acoustic emission while using these algorithms instead of the well-known threshold level method. Among these algorithms we study the methods based on hypothesis testing by probability ratio, which are described in [1], the algorithm based on the Schwarz Information Criteria (SIC) [2], the method using Singular Spectral Analysis (SSA) [4], and finally the algorithms based on the estimation of autoregressive stochastic processes (time series) and the consecutive chi^2 test [3]. As an example, applying these algorithms, we want to show some possible improvements of numerical iterative localization techniques for detecting the source of the acoustic emission. We con

Název v anglickém jazyce

Change point detection algorithms for complex physical dynamical systems

Popis výsledku anglicky

The target of this contribution is to present an integrated overview of algorithms which could be used for change point detection of any physical dynamical system, e.g. in acoustic system or for the particle detection in accelerated physics. Furthermorewe want to show a possible improvement of the localization of the source of acoustic emission while using these algorithms instead of the well-known threshold level method. Among these algorithms we study the methods based on hypothesis testing by probability ratio, which are described in [1], the algorithm based on the Schwarz Information Criteria (SIC) [2], the method using Singular Spectral Analysis (SSA) [4], and finally the algorithms based on the estimation of autoregressive stochastic processes (time series) and the consecutive chi^2 test [3]. As an example, applying these algorithms, we want to show some possible improvements of numerical iterative localization techniques for detecting the source of the acoustic emission. We con

Druh

D - Stať ve sborníku

CEP obor

BA - Obecná matematika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název statě ve sborníku

SPMS 2012 Proceedings

ISBN

978-80-01-05130-6

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

117-126

Název nakladatele

ČVUT

Místo vydání

Praha

Místo konání akce

Zlenice

Datum konání akce

25. 6. 2012

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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