Title :
Detecting abrupt changes in ARMA signals
Author :
Delaney, Kevin J. ; Therrien, Charles W.
Author_Institution :
US Naval Postgraduate Sch., Monterey, CA, USA
Abstract :
The authors describe a novel method for detecting changes in time series represented by autoregressive moving average models, based on a method by Nikiforov (see I.V. Nikiforov, 1986, I.V. Nikiforov and I.N. Tikhohov, 1986, and A.F. Kushnin et al., 1983). They review previous work by Nikiforov, describing a derivation of the sequential change detection method. The application of Nikiforov´s method to autoregressive models and its extension to ARMA models are described. Examples of the algorithm´s performance are given
Keywords :
signal processing; time series; ARMA signals; autoregressive moving average models; sequential change detection method; signal processing; time series; Additive noise; Autoregressive processes; Kalman filters; Maximum likelihood detection; Maximum likelihood estimation; Noise figure; Seismology; Sequential analysis; Signal processing; Speech processing;
Conference_Titel :
Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-2470-1
DOI :
10.1109/ACSSC.1991.186464
