DocumentCode
1490874
Title
Asymptotic normality of sample covariance matrix for mixed spectra time series: Application to sinusoidal frequencies estimation
Author
Delmas, Jean-Pierre
Author_Institution
Dept. Signal et Image, Inst. Nat. des Telecommun., Evry, France
Volume
47
Issue
4
fYear
2001
fDate
5/1/2001 12:00:00 AM
Firstpage
1681
Lastpage
1687
Abstract
This correspondence addresses the asymptotic normal distribution of the sample mean and the sample covariance matrix of mixed spectra time series containing a sum of sinusoids and a moving average (MA) process. Two central limit (CL) theorems are proved. As an application of this result, the asymptotic normal distribution of any sinusoidal frequencies estimator of such time series based on second-order statistics is deduced
Keywords
covariance matrices; frequency estimation; moving average processes; normal distribution; spectral analysis; time series; asymptotic normal distribution; asymptotic normality; central limit theorems; mixed spectra time series; moving average process; sample covariance matrix; sample mean; second-order statistics; sinusoidal frequencies estimation; sinusoidal frequencies estimator; sinusoids; Covariance matrix; Frequency estimation; Gaussian distribution; Random variables; Statistical distributions;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.923758
Filename
923758
Link To Document