Partial linearization of one class of the nonlinear total least squares problem by using the inverse model function

被引：22
|
作者：
Jukic, D
Scitovski, R
Späth, H
机构：
[1] Fac Food Technol, Dept Math, HR-31000 Osijek, Croatia
[2] Fac Elect Engn, Dept Math, HR-31000 Osijek, Croatia
[3] Carl von Ossietzky Univ Oldenburg, Fachbereich Math, D-26111 Oldenburg, Germany
来源：
COMPUTING | 1999年 / 62卷 / 02期
关键词：
nonlinear total least squares; errors in variables; orthogonal least squares fitting;
D O I：
10.1007/s006070050019
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper we consider a special nonlinear total least squares problem, where the model function is of the form f(x; a, b) = phi(-1) (ax + b). Using the fact that after an appropriate substitution, the model function becomes linear in parameters, and that the symmetry preserves the distances, this nonlinear total least squares problem can be greatly simplified. In this paper we give the existence theorem, propose an efficient algorithm for searching the parameters and give some numerical examples.
引用
收藏
页码：163 / 178
页数：16
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