Adaptive variable selection for extended Nijboer-Zernike aberration retrieval via lasso
文献类型:期刊论文
作者 | Wang, B.; H. A. Diao; J. H. Guo; X. Y. Liu and Y. H. Wu |
刊名 | Optics Communications
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出版日期 | 2017 |
卷号 | 385 |
英文摘要 | In 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. |
语种 | 英语 |
源URL | [http://ir.ciomp.ac.cn/handle/181722/59237] ![]() |
专题 | 长春光学精密机械与物理研究所_中科院长春光机所知识产出 |
推荐引用方式 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). |
入库方式: OAI收割
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