By Topic

Parameter estimation in the presence of non-Gaussian noise

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)
Salzwedel, H. ; Systems Control, Inc., Palo Alto, California

A method for parameter estimation is derived that is insensitive to the noise distribution, and an example of its use for nonlinear systems is given. The method combines the sensitivity of the maximum-likelihood parameter estimator with the robustness of order statistics to reduce estimation uncertainty significantly, with only a slight increase in the variance. This algorithm shows improvements over conventional parameter estimates, in particular, in the case of small data sets.

Published in:

Decision and Control including the Symposium on Adaptive Processes, 1980 19th IEEE Conference on

Date of Conference:

10-12 Dec. 1980