DocumentCode :
928275
Title :
Poisson sampling and spectral estimation of continuous-time processes
Author :
Masry, Elias
Volume :
24
Issue :
2
fYear :
1978
fDate :
3/1/1978 12:00:00 AM
Firstpage :
173
Lastpage :
183
Abstract :
A class of spectral estimates of continuous-time stationary stochastic processes 
from a finite number of observations 
taken at Poisson sampling instants 
is considered. The asymptotic bias and covariance of the estimates are derived, and the influence of the spectral windows and the sampling rate on the performance of the estimates is discussed. The estimates are shown to be consistent under mild smoothness conditions on the spectral density. Comparison is made with a related class of spectral estimates suggested in [15] where the number of observations is {em random}. It is shown that the periodograms of the two classes have distinct statistics.
from a finite number of observations taken at Poisson sampling instants is considered. The asymptotic bias and covariance of the estimates are derived, and the influence of the spectral windows and the sampling rate on the performance of the estimates is discussed. The estimates are shown to be consistent under mild smoothness conditions on the spectral density. Comparison is made with a related class of spectral estimates suggested in [15] where the number of observations is {em random}. It is shown that the periodograms of the two classes have distinct statistics.Keywords :
Poisson processes; Sampling methods; Spectral analysis; Time series; Density functional theory; Exponential distribution; Information science; Physics; Probability density function; Random variables; Sampling methods; Statistics; Stochastic processes; Time series analysis;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1978.1055858
Filename :
1055858
Link To Document :
