Treffer: Weight Least Squares Algorithm for Rational Models with Outliers: Weight least squares algorithm for rational models with outliers
Title:
Weight Least Squares Algorithm for Rational Models with Outliers: Weight least squares algorithm for rational models with outliers
Authors:
Source:
Complexity, Vol 2020 (2020)
Publisher Information:
Wiley, 2020.
Publication Year:
2020
Subject Terms:
0209 industrial biotechnology, Estimation and detection in stochastic control theory, Identification in stochastic control theory, 13. Climate action, Electronic computers. Computer science, 0202 electrical engineering, electronic engineering, information engineering, Nonlinear systems in control theory, QA75.5-76.95, 02 engineering and technology
Document Type:
Fachzeitschrift
Article
File Description:
application/xml; text/xhtml
Language:
English
ISSN:
1099-0526
1076-2787
1076-2787
DOI:
10.1155/2020/8963691
Access URL:
http://downloads.hindawi.com/journals/complexity/2020/8963691.pdf
https://zbmath.org/7199201
https://doi.org/10.1155/2020/8963691
https://doaj.org/article/7a50a66814fe493d98fe9d8e1d337694
https://dblp.uni-trier.de/db/journals/complexity/complexity2020.html#LvL20
https://philpapers.org/rec/LVWLS
https://ideas.repec.org/a/hin/complx/8963691.html
https://www.hindawi.com/journals/complexity/2020/8963691/
https://downloads.hindawi.com/journals/complexity/2020/8963691.pdf
https://zbmath.org/7199201
https://doi.org/10.1155/2020/8963691
https://doaj.org/article/7a50a66814fe493d98fe9d8e1d337694
https://dblp.uni-trier.de/db/journals/complexity/complexity2020.html#LvL20
https://philpapers.org/rec/LVWLS
https://ideas.repec.org/a/hin/complx/8963691.html
https://www.hindawi.com/journals/complexity/2020/8963691/
https://downloads.hindawi.com/journals/complexity/2020/8963691.pdf
Rights:
CC BY
Accession Number:
edsair.doi.dedup.....b8e22489cc8df895d2b1dcffc8dd941f
Database:
OpenAIRE
Weitere Informationen
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.