Weight Least Squares Algorithm for Rational Models with Outliers

A weight least squares algorithm is developed for rational models with outliers in this paper. Different weights are assigned for each cost function, and by calculating the derivatives of these cost functions, the parameter estimates can be estimated. Compared with the traditional least squares algo...

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Main Authors: Lixin Lv, Donglei Lu
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/8963691
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author Lixin Lv
Donglei Lu
author_facet Lixin Lv
Donglei Lu
author_sort Lixin Lv
collection DOAJ
description A weight least squares algorithm is developed for rational models with outliers in this paper. Different weights are assigned for each cost function, and by calculating the derivatives of these cost functions, the parameter estimates can be estimated. Compared with the traditional least squares algorithm, the proposed algorithm can remove the bad effect caused by the outliers, thus has more accurate parameter estimates. A simulation example is proposed to validate the effectiveness of the proposed algorithm.
format Article
id doaj-art-7a50a66814fe493d98fe9d8e1d337694
institution OA Journals
issn 1076-2787
1099-0526
language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-7a50a66814fe493d98fe9d8e1d3376942025-08-20T02:07:36ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/89636918963691Weight Least Squares Algorithm for Rational Models with OutliersLixin Lv0Donglei Lu1Wuxi Vocational College of Science and Technology, Wuxi 214028, ChinaWuxi Vocational College of Science and Technology, Wuxi 214028, ChinaA weight least squares algorithm is developed for rational models with outliers in this paper. Different weights are assigned for each cost function, and by calculating the derivatives of these cost functions, the parameter estimates can be estimated. Compared with the traditional least squares algorithm, the proposed algorithm can remove the bad effect caused by the outliers, thus has more accurate parameter estimates. A simulation example is proposed to validate the effectiveness of the proposed algorithm.http://dx.doi.org/10.1155/2020/8963691
spellingShingle Lixin Lv
Donglei Lu
Weight Least Squares Algorithm for Rational Models with Outliers
Complexity
title Weight Least Squares Algorithm for Rational Models with Outliers
title_full Weight Least Squares Algorithm for Rational Models with Outliers
title_fullStr Weight Least Squares Algorithm for Rational Models with Outliers
title_full_unstemmed Weight Least Squares Algorithm for Rational Models with Outliers
title_short Weight Least Squares Algorithm for Rational Models with Outliers
title_sort weight least squares algorithm for rational models with outliers
url http://dx.doi.org/10.1155/2020/8963691
work_keys_str_mv AT lixinlv weightleastsquaresalgorithmforrationalmodelswithoutliers
AT dongleilu weightleastsquaresalgorithmforrationalmodelswithoutliers