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

Comparisons of stochastic gradient and least squares algorithms for multivariable systems

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

3 Author(s)
Yuwu Liao ; Dept. of Phys. & Electron. Inf. Technol., Xiangfan Univ., Xiangfan, China ; Yanjun Liu ; Feng Ding

Two identification models are obtained for multivariable ARX systems by different parameterization, and the corresponding two least squares and two stochastic gradient algorithms are given based on the lest squares principle and the stochastic gradient search principle and minimizing different cost functions. The performances of these algorithms are analyzed and compared by the simulation tests.

Published in:

Control and Decision Conference (CCDC), 2010 Chinese

Date of Conference:

26-28 May 2010

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.