By Topic

Estimation of continuous-time autoregressive model from finely sampled data

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)
Dinh-Tuan Pham ; Lab. of Modeling. & Comput., CNRS, Grenoble, France

We extend our two earlier continuous-time estimation methods for continuous-time autoregressive (CAR) model to derive estimators using only finely sampled discrete-time data. The approach is based on the approximation of derivatives by divided differences, coupled with some bias correction. Two types of estimators are provided, having bias of the order O(h) or of O(h2) respectively, for small sampling interval h. The procedures are computationally efficient and always yield a stable autoregressive polynomial. Simulations show that their bias are quite low

Published in:

Signal Processing, IEEE Transactions on  (Volume:48 ,  Issue: 9 )