Statistical properties of exponentially weighted moving average algorithm for change detection

Author

Chitraganti, Shaikshavali ; Aberkane, S. ; Aubrun, Christophe

Author_Institution

Centre de Rech. en Autom. de Nancy (CRAN), Univ. de Lorraine, Vandoeuvre-les-Nancy, France

fYear

2012

fDate

10-13 Dec. 2012

Firstpage

574

Lastpage

578

Abstract

In this paper, the statistical properties of a change detection algorithm are considered. More specifically, we considered the exponentially weighted moving average (EWMA) algorithm. Analytical expressions for the probability distribution of detection delay and the time between false alarms are proposed, and the results are validated by simulations. The results can be used in examining the abrupt changes in a signal, and also in the design of active fault tolerant control systems.

Keywords

control system synthesis; delays; fault tolerance; moving average processes; statistical distributions; AFTCS design; EWMA algorithm; active fault tolerant control systems; change detection algorithm; detection delay; exponentially weighted moving average algorithm; false alarms; probability distribution; statistical properties; Delay; Detection algorithms; Fault detection; Fault tolerance; Markov processes; Probability density function; Yttrium;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control (CDC), 2012 IEEE 51st Annual Conference on

Conference_Location

Maui, HI

ISSN

0743-1546

Print_ISBN

978-1-4673-2065-8

Electronic_ISBN

0743-1546

Type

conf

DOI

10.1109/CDC.2012.6426477

Filename

6426477