Sign CUSUM Algorithm for Change-Point Detection of the MMPP Controlling Chain State

Podrobná bibliografie
Parent link:Communications in Computer and Information Science
Vol. 638 : Information Technologies and Mathematical Modelling - Queueing Theory and Applications, ITMM 2016.— 2014.— [P. 18-33]
Hlavní autor: Burkatovskaya Yu. B. Yuliya Borisovna
Korporativní autor: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра вычислительной техники (ВТ)
Další autoři: Kbanova T. V. Tatjyana Vladimirovna, Tokareva O. S. Olga Sergeevna
Shrnutí:Title screen
The authors consider the Markov modulated Poisson process with two states of the Markovian controlling chain. The flow intensity of the observed process depends on the unobserved controlling chain state. All the process parameters are supposed to be unknown. The paper develops a new sequential change-point detection method based on the cumulative sum control chart approach to determine the switching points of the flow intensity. Usage of special sign statistics allows the obtaining of theoretical characteristics of the proposed algorithm.
Режим доступа: по договору с организацией-держателем ресурса
Jazyk:angličtina
Vydáno: 2014
Témata:
On-line přístup:http://dx.doi.org/10.1007/978-3-319-44615-8_2
Médium: Elektronický zdroj Kapitola
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=650785

MARC

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330 |a The authors consider the Markov modulated Poisson process with two states of the Markovian controlling chain. The flow intensity of the observed process depends on the unobserved controlling chain state. All the process parameters are supposed to be unknown. The paper develops a new sequential change-point detection method based on the cumulative sum control chart approach to determine the switching points of the flow intensity. Usage of special sign statistics allows the obtaining of theoretical characteristics of the proposed algorithm. 
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