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ontheseparablenonlinearleastsquaresproblems
Xin Liu1; Yaxiang Yuan2
2008
Source Publicationjournalofcomputationalmathematics
ISSN0254-9409
Volume26Issue:3Pages:390
AbstractSeparable nonlinear least squares problems are a special class of nonlinear least squares problems, where the objective functions are linear and nonlinear on different parts of variables. Such problems have broad applications in practice. Most existing algorithms for this kind of problems are derived from the variable projection method proposed by Golub and Pereyra, which utilizes the separability under a separate framework. However, the methods based on variable projection strategy would be invalid if there exist some constraints to the variables, as the real problems always do, even if the constraint is simply the ball constraint. We present a new algorithm which is based on a special approximation to the Hessian by noticing the fact that certain terms of the Hessian can be derived from the gradient. Our method maintains all the advantages of variable projection based methods, and moreover it can be combined with trust region methods easily and can be applied to general constrained separable nonlinear problems. Convergence analysis of our method is presented and numerical results are also reported.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/38543
Collection中国科学院数学与系统科学研究院
Affiliation1.中国科学院数学研究所
2.中国科学院数学与系统科学研究院
Recommended Citation
GB/T 7714
Xin Liu,Yaxiang Yuan. ontheseparablenonlinearleastsquaresproblems[J]. journalofcomputationalmathematics,2008,26(3):390.
APA Xin Liu,&Yaxiang Yuan.(2008).ontheseparablenonlinearleastsquaresproblems.journalofcomputationalmathematics,26(3),390.
MLA Xin Liu,et al."ontheseparablenonlinearleastsquaresproblems".journalofcomputationalmathematics 26.3(2008):390.
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