By Topic

Estimation with maximum error requirements

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
$33 $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

2 Author(s)
Ben-Haim, Z. ; Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel ; Eldar, Y.C.

We consider the problem of estimating a deterministic parameter vector x from observations y = Hx + w. where H is known and w is additive noise. We seek an estimator whose estimation error is within given limits, for as wide a range of conditions as possible. The error limit is a design choice, and is generally lower than the error provided by the well-known least-squares (LS) estimator. We develop estimators guaranteeing the required error for as large a parameter set as possible, and for as large a noise level as possible. We discuss methods for finding these estimators, and demonstrate that in many cases, the proposed estimators outperform the LS estimator.

Published in:

Electrical and Electronics Engineers in Israel, 2004. Proceedings. 2004 23rd IEEE Convention of

Date of Conference:

6-7 Sept. 2004