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Adaptive variable selection for extended Nijboer-Zernike aberration retrieval via lasso
Wang, B.; H. A. Diao; J. H. Guo; X. Y. Liu and Y. H. Wu
2017
Source PublicationOptics Communications
Volume385
AbstractIn this paper, we propose extended Nijboer-Zernike (ENZ) method for aberration retrieval by incorporating lasso variable selection method which can improve the accuracy of aberration retrieval. The proposed model is computed by the state-of-art algorithm of the Bregman iterative algorithm (Bregman, 1967 [1]; Cai et al., 2008 [2]; Yin et al., 2008 [3]) for L-1 minimization problem with adaptive regularized parameter choice based on the strategy (Ito et al., 2011 [4]). Numerical simulations for real world and simulated phase data validate the effectiveness of the proposed ENZ AR via lasso.
Indexed Bysci ; ei
Language英语
Document Type期刊论文
Identifierhttp://ir.ciomp.ac.cn/handle/181722/59237
Collection中科院长春光机所知识产出
Recommended Citation
GB/T 7714
Wang, B.,H. A. Diao,J. H. Guo,et al. Adaptive variable selection for extended Nijboer-Zernike aberration retrieval via lasso[J]. Optics Communications,2017,385.
APA Wang, B.,H. A. Diao,J. H. Guo,&X. Y. Liu and Y. H. Wu.(2017).Adaptive variable selection for extended Nijboer-Zernike aberration retrieval via lasso.Optics Communications,385.
MLA Wang, B.,et al."Adaptive variable selection for extended Nijboer-Zernike aberration retrieval via lasso".Optics Communications 385(2017).
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