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|
|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. https://doi.org/10.1007/s10915-008-9231-7|
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on May 12, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.