Title :
Spectral estimation of nonstationary time series
Author :
Moore, A. ; McLaughlin, S.
Author_Institution :
Edinburgh Univ., UK
Abstract :
The spectral estimation of nonstationary time series is a long standing problem of major importance. Examples of such time series can be drawn from many diverse fields such a communications, foetal heart rate and condition monitoring. The time series involved can be nonstationary in mean, covariance or both. The authors examine a time series which is artificially generated and can have either a slowly or a rapidly changing spectrum. Attempts are made to model such time series using two different techniques so that their spectra may be estimated. The trade-offs involved in using the two different modelling techniques are then discussed
Keywords :
filtering and prediction theory; parameter estimation; spectral analysis; time series; autoregressive model; linear prediction; modelling; nonstationary time series; rapidly changing spectrum; slowly changing spectrum; spectral estimation;
Conference_Titel :
Digital Processing of Signals in Communications, 1991., Sixth International Conference on
Conference_Location :
Loughborough
Print_ISBN :
0-85296-522-2