DocumentCode
851599
Title
Detection of changes in the spectrum of a multidimensional process
Author
Lavielle, Marc
Author_Institution
Univ. Paris-Sud, Orsay, France
Volume
41
Issue
2
fYear
1993
fDate
2/1/1993 12:00:00 AM
Firstpage
742
Lastpage
749
Abstract
An algorithm is presented for the sequential detection of changes in the spectrum of a multidimensional process. The asymptotic properties of the statistic used are investigated in the case of a real Gaussian process. The algorithm of detection is based on a sequential likelihood-ratio test. Simulations show very good behavior of the algorithm in the case of Gaussian and non-Gaussian processes. In both cases, changes are detected with good accuracy, while the number of false alarms is small
Keywords
Monte Carlo methods; random processes; spectral analysis; Monte Carlo simulation; Non Gaussian process; asymptotic properties; false alarms; multidimensional process; real Gaussian process; sequential detection; sequential likelihood-ratio test; spectrum change detection; Acoustic signal detection; Acoustic waves; Change detection algorithms; Distribution functions; Gaussian processes; Multidimensional systems; Sequential analysis; Statistical distributions; Statistics; Stochastic processes;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.193214
Filename
193214
Link To Document