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Recursive Variable Projection Algorithm for a Class of Separable Nonlinear Models
Gan, Min1; Guan, Yu2; Chen, Guang Yong3; Philip Chen, C. L.4
2021-11-01
Source PublicationIEEE Transactions on Neural Networks and Learning Systems
ISSN2162-237X
Volume32Issue:11Pages:4971-4982
Abstract

In this article, we study the recursive algorithms for a class of separable nonlinear models (SNLMs) in which the parameters can be partitioned into a linear part and a nonlinear part. Such models are very common in machine learning, system identification, and signal processing. Utilizing the special structure of the SNLMs, we propose a recursive variable projection (RVP) algorithm, in which at each recursion, the linear parameters of the model are eliminated, and the nonlinear parameters are updated by the recursive Levenberg-Marquart algorithm. Then, based on the updated nonlinear parameters, the linear parameters are updated by the recursive least-squares algorithm. According to a convergence analysis of the RVP algorithm, the parameter estimation error is mean-square bounded. Numerical examples confirm the satisfactory performance of the proposed algorithm.

KeywordOnline Learning Recursive Identification Separable Nonlinear Models (Snlms) Variable Projection (Vp)
DOI10.1109/TNNLS.2020.3026482
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000711638200020
Scopus ID2-s2.0-85118987601
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Cited Times [WOS]:15   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorChen, Guang Yong
Affiliation1.College of Computer Science and Technology, Qingdao University, Qingdao, 266071, China
2.College of Mathematics and Computer Science, Fuzhou University, Fuzhou, 350108, China
3.Faculty of Science and Technology, University of Macau, Macao
4.School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510641, China
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Gan, Min,Guan, Yu,Chen, Guang Yong,et al. Recursive Variable Projection Algorithm for a Class of Separable Nonlinear Models[J]. IEEE Transactions on Neural Networks and Learning Systems,2021,32(11):4971-4982.
APA Gan, Min,Guan, Yu,Chen, Guang Yong,&Philip Chen, C. L..(2021).Recursive Variable Projection Algorithm for a Class of Separable Nonlinear Models.IEEE Transactions on Neural Networks and Learning Systems,32(11),4971-4982.
MLA Gan, Min,et al."Recursive Variable Projection Algorithm for a Class of Separable Nonlinear Models".IEEE Transactions on Neural Networks and Learning Systems 32.11(2021):4971-4982.
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