Asymptotic normality of sample autocovariances with an application in frequency estimation

Stochastic Processes and their Applications

Volumn 52, Issue 2, 1994, Pages 329-349

  Li, Ta Hsin ^a,b   Kedem, Benjamin ^b   Yakowitz, Sid ^c  

^a TEXAS A AND M UNIVERSITY   (United States)

^b UNIVERSITY OF MARYLAND   (United States)

^c UNIVERSITY OF ARIZONA   (United States)

Author keywords

Asymptotic normality; Autocovariance; Filter; Frequency estimation; Mixed spectrum; Spectral analysis; Time series

Indexed keywords

EID: 0000696717     PISSN: 03044149     EISSN: None     Source Type: Journal    
DOI: 10.1016/0304-4149(94)90032-9     Document Type: Article

References (18)

1. The maximum of the periodogram
2. Martingale central limit theorems
3. Higher-order crossings of an almost periodic random sequence in noise
4. The zero-crossing rate of autoregressive processes and its link to unit roots
5. Spectrum analysis — A modern perspective
6. Contraction mappings in mixed spectrum estimation
7. Strong consistency of the contraction mapping method for frequency estimation
8. Some properties of autoregressive estimates for processes with mixed spectra
9. A fast efficient technique for the estimation of frequency
10. On frequency estimation
11. Maximum likelihood estimation of the parameters of multiple sinusoids from noisy measurements
12. Overdetermined Yule-Walker estimation of the frequencies of multiple sinusoids: accuracy aspects
13. A new approach to frequency analysis with amplified harmonics
14. On the estimation of a harmonic component in a time series with stationary independent residuals
15. Some contribution to a frequency location method due to He and Kedem
16. Asymptotic theory for a fast frequency detector