Comparison of Structured and Weighted Total Least-Squares Adjustment Methods for Linearly Structured Errors-in-Variables Models
Comparison of Structured and Weighted Total Least-Squares Adjustment Methods for Linearly Structured Errors-in-Variables Models
复制标题
线性结构化变量误差模型的结构化和加权总体最小二乘调整方法的比较
DOI：
10.1061/(asce)su.1943-5428.0000190
复制
发表时间：
2017-02
影响因子：
1.9
通讯作者：
Fang Xing
中科院分区：
文献类型：
--
作者：
Zhou Yongjun;Kou Xinjian;Li Jonathan;Fang Xing
摘要
本文聚焦于一种特定的变量误差（EIV）模型，即线性结构变量误差（LSEIV）模型，在该模型中，设计矩阵的所有随机元素是带有随机误差的输入向量的线性组合。两种现有的结构……
AbstractThe paper focuses on a specific errors-in-variables (EIV) model named the linearly structured EIV (LSEIV) model in which all the random elements of design matrix are in a linear combination of an input vector with random errors. Two existing structured total least-squares (STLS) algorithms named constrained TLS (CTLS) and structured TLS normalization (STLN) are introduced to solve the LSEIV model by treating the input and output vectors as the noisy structure vectors. For comparison purposes, the weighted TLS (WTLS) method is also performed based on the partial EIV model. Approximated accuracy assessment methods are also presented. The plane fitting and Bursa transformation examples are illustrated to demonstrate the accuracy and computational efficiency performance of the proposed algorithms. It shows that the proposed STLS and WTLS algorithms can achieve the same accuracy if the dispersion matrix of the WTLS method is constructed based on the partial EIV model.
登录
查看更多内容
影响因子：
2.5
作者：
Y. Felus
通讯作者：
Y. Felus
DOI：
10.5281/zenodo.35986
发表时间：
1996
期刊：
1996 8th European Signal Processing Conference (EUSIPCO 1996)
影响因子：
--
作者：
P. Lemmerling;S. Huffel;B. Moor
通讯作者：
P. Lemmerling;S. Huffel;B. Moor
影响因子：
4.4
作者：
Markovsky, Ivan;Van Huffel, Sabine
通讯作者：
Van Huffel, Sabine
影响因子：
4.4
作者：
Yunzhong Shen;Bofeng Li;Yi Chen
通讯作者：
Yunzhong Shen;Bofeng Li;Yi Chen
影响因子：
0.9
作者：
Yongjun Zhou;X. Kou;Jianjun Zhu;Jonathan Li
通讯作者：
Yongjun Zhou;X. Kou;Jianjun Zhu;Jonathan Li