By Topic

Poisson sampling and spectral estimation of continuous-time processes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)

A class of spectral estimates of continuous-time stationary stochastic processesX(t)from a finite number of observations{X(t_{n})}^{N}_{n}=ltaken at Poisson sampling instants{t_{n}}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.

Published in:

Information Theory, IEEE Transactions on  (Volume:24 ,  Issue: 2 )