Spectral bandwidth correction with optimal parameters based on deep learning
文献类型：期刊论文
| 作者 | Cui, Hao1,2,3; Xia, Guo1,2,3; Huang, Chan4; Wang, Jiangtao1,2,3; Bai, Lihao1,2,3 |
| 刊名 | APPLIED OPTICS
 |
| 出版日期 | 2021-02-10 |
| 卷号 | 60 |
| ISSN号 | 1559-128X |
| DOI | 10.1364/AO.412526 |
| 通讯作者 | Xia, Guo(xiaguo@hfut.edu.cn) |
| 英文摘要 | Spectral bandwidth correction is an effective way to obtain the original spectrum. However, the correct selection of optimal parameters used to recover the distortion spectrum in bandwidth correction algorithms has always been an important problem. To overcome the shortcomings of traditional parameter selection methods and obtain the optimal parameter, we propose a new optimal parameter selection method based on deep learning (DL). First, the database and neural network were constructed, and then the optimal parameters of corresponding algorithms were obtained through the training of the neural network. In order to verify the superiority of the optimal parameter selection method based on DL, the Levenberg-Marquardt (L-M) and Richardson-Lucy (R-L) algorithms with corresponding optimal parameters were compared with the traditional L-M and R-L algorithms to recover the distortion white light-emitting diode, Raman spectrum, and compact fluorescent lamp spectrum. The type A uncertainty and root mean square error values of the different cases were calculated. The results proved that, compared with the traditional methods for obtaining the optimal parameters, the neural network was capable of obtaining parameters that can make the bandwidth correction algorithm more efficient at recovering the distorted spectrum. (C) 2021 Optical Society of America |
| WOS关键词 | ALGORITHM ; SPECTROMETER ; DECONVOLUTION |
| 资助项目 | Key Research and Development Program of Anhui Province[1804d08020310] |
| WOS研究方向 | Optics |
| 语种 | 英语 |
| WOS记录号 | WOS:000617545500027 |
| 出版者 | OPTICAL SOC AMER |
| 资助机构 | Key Research and Development Program of Anhui Province |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/120487]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Xia, Guo |
| 作者单位 | 1.Hefei Univ Technol, Acad Optoelect Technol, Hefei, Peoples R China 2.Special Display & Imaging Technol Innovat Ctr Anh, Hefei, Peoples R China 3.State Key Lab Adv Display Technol, Hefei, Peoples R China 4.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei 230031, Anhui, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cui, Hao,Xia, Guo,Huang, Chan,et al. Spectral bandwidth correction with optimal parameters based on deep learning[J]. APPLIED OPTICS,2021,60. |
| APA | Cui, Hao,Xia, Guo,Huang, Chan,Wang, Jiangtao,&Bai, Lihao.(2021).Spectral bandwidth correction with optimal parameters based on deep learning.APPLIED OPTICS,60. |
| MLA | Cui, Hao,et al."Spectral bandwidth correction with optimal parameters based on deep learning".APPLIED OPTICS 60(2021). |
入库方式： OAI收割
来源：合肥物质科学研究院
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