Model Introduced SPRT for Structural Change Detection of Time Series (II)

被引：6

作者：

Koyama, Yoshihide ^{[1
]}

Hattori, Tetsuo ^{[1
]}

Takeda, Katsunori ^{[2
]}

Kawano, Hiromichi ^{[3
]}

机构：

[1] Kagawa Univ, Grad Sch Engn, 2217-20 Hayashi, Takamatsu, Kagawa 7610396, Japan

[2] Canon IT Solutions Inc, Nishi Ku, Osaka Shi 5500001, Japan

[3] NTT Adv Technol, Tokyo 1800006, Japan

来源：

JOURNAL OF ROBOTICS NETWORKING AND ARTIFICIAL LIFE | 2014年 / 1卷 / 03期

关键词：

Change detection; SPRT; NSPR; Hidden Markov Model; Information Theory; Binary Channel; Bayes' Updating;

D O I：

10.2991/jrnal.2014.1.3.14

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

In this paper, using the notion of a binary Channel Matrix as well known in Information Theory, we present an equivalent relation between the SPRT (Sequential Probability Ratio Test) and Bayes' Updating. Moreover, we show the relationship between the SPRT and NSPR (New Sequential Probability Ratio) where a Hidden Markov Model with Poisson process is introduced as structural change model. And we also provide the change point detection performance of SPRT and NSPR by experimental results.

引用

页码：237 / 243

页数：7

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