Please use this identifier to cite or link to this item:
Title: A robust high-order mixed L2-linfty estimation for linear-in-the-parameters models
Authors: Zhu, Q.
Qiao, Y.
Tan, S. 
Keywords: High-order
Parameter estimation
System identification
Issue Date: Feb-2009
Citation: Zhu, Q., Qiao, Y., Tan, S. (2009-02). A robust high-order mixed L2-linfty estimation for linear-in-the-parameters models. Journal of Scientific Computing 38 (2) : 185-206. ScholarBank@NUS Repository.
Abstract: A new algorithm called Mixed L2-Linfty (ML2) estimation is proposed in this paper; it combines both the weighted least squares and the worst-case parameter estimations together as the cost function and strikes the right balance between them. A robust ML2 algorithm and a practical approximate robust ML2 algorithm are also developed under disturbance signals. The properties of the new robust ML2 algorithm are analyzed and the simulation results are given to show the convergence and the validity. © 2008 Springer Science+Business Media, LLC.
Source Title: Journal of Scientific Computing
ISSN: 08857474
DOI: 10.1007/s10915-008-9231-7
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

checked on Nov 24, 2022

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.