Constrained logarithmic least squares in parameter estimation

被引：6

作者：

Bai, EW ^{[1
]}

Ye, YY

机构：

[1] Univ Iowa, Dept Elect & Comp Engn, Iowa City, IA 52242 USA

[2] Univ Iowa, Dept Management Sci, Iowa City, IA 52242 USA

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1999年 / 44卷 / 01期

基金：

美国国家科学基金会;

关键词：

least squares; parameter estimation; system identification;

D O I：

10.1109/9.739123

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 [计算机科学与技术];

摘要：

The contribution of this paper is twofold. First, it is shown that while robust in terms of the average output error, the least squares estimate is sensitive to outliers with respect to the maximum output error. In fact the worst case output error of the least squares can go unbounded. Then, a constrained logarithmic least squares for system identification is proposed. Analytic center algorithms are presented to solve this constrained logarithmic least squares problem.

引用

页码：182 / 186

页数：5

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