Detail publikačního výsledku

Bayesian change detection in the growing window recursive strategy

DOKOUPIL, J.; VÁCLAVEK, P.

Originální název

Bayesian change detection in the growing window recursive strategy

Anglický název

Bayesian change detection in the growing window recursive strategy

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

A novel growing-window recursive algorithm for stochastic system change detection is derived based on the Bayesian inference principle. Model based detectors can be formalized by two concepts in literature: (a) working in a sliding-window strategy because of time-dependent computational complexity, or (b) running in parallel, each one matched to a certain assumption on a change point. This motivates us to investigate a more refined approach which utilizes all relevant data to catch the next change point. The basic idea is to formulate a distance measure between two probabilities, one confirming the change occurrence and the other confirming no change in the system behavior. This study aims to solve the difficulty of sliding time arguments in the compared probabilities as new data are sequentially obtained. The outcome of this analysis is an algorithm that recognizes the time and magnitude of the change occurrence.

Anglický abstrakt

A novel growing-window recursive algorithm for stochastic system change detection is derived based on the Bayesian inference principle. Model based detectors can be formalized by two concepts in literature: (a) working in a sliding-window strategy because of time-dependent computational complexity, or (b) running in parallel, each one matched to a certain assumption on a change point. This motivates us to investigate a more refined approach which utilizes all relevant data to catch the next change point. The basic idea is to formulate a distance measure between two probabilities, one confirming the change occurrence and the other confirming no change in the system behavior. This study aims to solve the difficulty of sliding time arguments in the compared probabilities as new data are sequentially obtained. The outcome of this analysis is an algorithm that recognizes the time and magnitude of the change occurrence.

Klíčová slova

Bayesian inference, change point probabilities, multiple change points

Klíčová slova v angličtině

Bayesian inference, change point probabilities, multiple change points

Autoři

DOKOUPIL, J.; VÁCLAVEK, P.

Rok RIV

2016

Vydáno

21.07.2015

Nakladatel

Trans Tech Publications Ltd

Místo

Německo

ISBN

978-3-03835-499-4

Kniha

Applied mechanics and materials

ISSN

1660-9336

Periodikum

Applied Mechanics and Materials

Svazek

775

Stát

Švýcarská konfederace

Strany od

399

Strany do

403

Strany počet

4

URL

http://www.scientific.net/AMM.775.399

BibTex

@inproceedings{BUT117762,
  author="Jakub {Dokoupil} and Pavel {Václavek}",
  title="Bayesian change detection in the growing window recursive strategy",
  booktitle="Applied mechanics and materials",
  year="2015",
  journal="Applied Mechanics and Materials",
  volume="775",
  pages="399--403",
  publisher="Trans Tech Publications Ltd",
  address="Německo",
  doi="10.1063/1.4912383",
  isbn="978-3-03835-499-4",
  issn="1660-9336",
  url="http://www.scientific.net/AMM.775.399"
}