The New Approach to the Detection of the Abrupt Change of Fast Fluctuating Random Processes in the Conditions of Parametric Prior Uncertainty

DOI

10.2991/acta-14.2014.3How to use a DOI?

Keywords

random process; abrupt change; detection; maximum likelihood method; parametrical prior uncertainty; local Markov approximation method; statistical computer modeling.

Abstract

In this study work we introduce a technically simple way of the detection of an abrupt change in parameters of fast fluctuating Gaussian processes in the conditions of parametric prior uncertainty. For this purpose, we suggest new approximations of solving statistics under various hypotheses. As an example of the mathematical expectation jumping of a random process, the appropriate detection algorithm is synthesized and the method of finding of the analytical expressions for the characteristics of its operating effectiveness is illustrated. Applying statistical computer modeling, we have found that the proposed method of the detection of the abrupt changes in parameters of fast-fluctuating random processes is operable, and the theoretical formulas for the detection characteristics well conform with the corresponding experimental data in a wide range of parameter values of the analyzed process.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Oleg V. Chernoyarov
AU  - Boris I. Shakhtarin
AU  - Alexander P. Ermakov
AU  - Dmitry K. Proskurin
PY  - 2014/06
DA  - 2014/06
TI  - The New Approach to the Detection of the Abrupt Change of Fast Fluctuating Random Processes in the Conditions of Parametric Prior Uncertainty
BT  - 2014 International Conference on Automatic Control Theory and Application
PB  - Atlantis Press
SP  - 9
EP  - 13
SN  - 2352-5398
UR  - https://doi.org/10.2991/acta-14.2014.3
DO  - 10.2991/acta-14.2014.3
ID  - Chernoyarov2014/06
ER  -