Web projektu DAR

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Data - Algoritmy - Rozhodování

Založeno v roce 2005 s podporou MŠMT ČR (projekt 1M0572)

Publikace

Smoothing in Multiple Model Change Detection for Stochastic Systems

Typ:

Konferenční příspěvek

Autoři publikace:

Punčochář I., Duník J., Šimandl M.

Název sborniku:

Proceedings of the 8th ACD 2010 European Workshop on Advanced Control and Diagnosis

Místo vydání:

Ferrara, Italy

Rok:

2010

Strany:

79-84

Kontaktní osoba:

Ing. Ivo Punčochář, Ph.D. (FAV Západočeská univerzita, katedra kybernetiky)

Klíčová slova:

Stochastic systems, detection systems, change detection

Adresa (www stránky):

http://www.ing.unife.it/eventi/ACD2010/

příloha1:

ADC10_IP.pdf [file]

příloha2:

prezentace_ADC10_IP.pdf [file]

Anotace:

The paper focuses on the application of smoothing in multiple model change detection for stochastic systems. In a typical multiple model change detection scheme, the decisions are made based on ?ltering estimates of an unmeasured state of an observed system. Since better estimates of the state lead to ?ner decisions, a higher quality of estimates is of great interest. The way to improve the decisions considered in this paper consists in deferring decisions and using more precise smoothing estimates instead of the ?ltering ones. As a result, the decisions of a higher quality are obtained at the cost of delaying that decisions. The approach introduces a new level of the compromise between the quality of decisions and the delay for detection that is inherent in all change detection methods.