Cart (Loading....) | Create Account
Close category search window

A new recursive least-squares identification algorithm based on singular value decomposition

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

4 Author(s)
Youmin Zhang ; Dept. of Autom. Control, Northwestern Polytech. Univ., Xian, China ; Qingguo Li ; Guanzhong Dai ; Hongcai Zhang

Based on singular value decomposition (SVD), a new recursive least-squares identification method, which takes in account input excitation, is proposed in this paper. It is demonstrated that the SVD-based approach proposed in this paper can not only obviously improve the convergence rate, numerical stability of RLS, but also provide much more precise identification results and greatly enhance the robustness of the system identification. Moreover, this algorithm is formulated in the form of vector-matrix and matrix-matrix operations, so it is also useful for parallel computers

Published in:

Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on  (Volume:2 )

Date of Conference:

14-16 Dec 1994

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.