Abstract
Page's test is optimal in quickly detecting distributional changes among independent observations. In this paper we propose a similar procedure for the quickest detection of dependent signals which can be conveniently modeled as Hidden Markov Models. Considering Page's test as a repeated sequential probability ratio test (SPRT), we use Wald's approximation, with modification regarding the threshold overshoot, to predict the performance of the test, namely the average run length (ARL) between false alarms, T. Using the asymptotic convergence property of the test statistic, we are also able to predict the ARL to detection, D. Analysis shows T is asymptotically exponential in D, as in the i.i.d. case. The results are supported by numerical examples.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the IEEE Conference on Decision and Control |
| Editors | Anon |
| Publisher | IEEE Computer Society |
| Pages | 3984-3989 |
| Number of pages | 6 |
| Volume | 4 |
| State | Published - 1997 |
| Externally published | Yes |
| Event | Proceedings of the 1997 36th IEEE Conference on Decision and Control. Part 1 (of 5) - San Diego, CA, USA Duration: Dec 10 1997 → Dec 12 1997 |
Other
| Other | Proceedings of the 1997 36th IEEE Conference on Decision and Control. Part 1 (of 5) |
|---|---|
| City | San Diego, CA, USA |
| Period | 12/10/97 → 12/12/97 |
ASJC Scopus subject areas
- Chemical Health and Safety
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality