Maximum correntropy criterion based regression for multivariate calibration | |
Peng, Jiangtao1; Guo, Lu1; Hu, Yong2; Rao, KaiFeng3; Xie, Qiwei4,5 | |
刊名 | CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS |
2017-02-15 | |
卷号 | 161页码:27-33 |
关键词 | Maximum Correntropy Criterion Least-squares Multivariate Calibration Regularization |
DOI | 10.1016/j.chemolab.2016.12.002 |
文献子类 | Article |
英文摘要 | The least-squares criterion is widely used in the multivariate calibration models. Rather than using the conventional linear least-squares metric, we employ a nonlinear correntropy-based metric to describe the spectra-concentrate relations and propose a maximum correntropy criterion based regression (MCCR) model. To solve the correntropy-based model, a half-quadratic optimization technique is developed to convert a non convex and nonlinear optimization problem into an iteratively re-weighted least-squares problem. Finally, MCCR can provide an accurate estimation of the regression relation by alternatively updating an auxiliary vector represented as a nonlinear Gaussian function of fitted residuals and a weight computed by a regularized weighted least-squares model. The proposed method is Compared to some modified PLS algorithms and robust regression methods on four real near-infrared (NIR) spectra data sets. Experimental results demonstrate the efficacy and effectiveness of the proposed method. |
WOS关键词 | LEAST-SQUARES REGRESSION ; CONTINUUM REGRESSION |
WOS研究方向 | Automation & Control Systems ; Chemistry ; Computer Science ; Instruments & Instrumentation ; Mathematics |
语种 | 英语 |
WOS记录号 | WOS:000394066100004 |
资助机构 | National Natural Science Foundation of China(41501392 ; Natural Science Foundation of Hubei Province(2009CDB387) ; trategic Priority Research Program of the CAS(XDB02060001) ; State Key Joint Laboratory of Environment Simulation and Pollution Control(15K02ESPCR) ; 11371007) |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/14400] |
专题 | 自动化研究所_类脑智能研究中心 |
作者单位 | 1.Hubei Univ, Fac Math & Stat, Hubei Key Lab Appl Math, Wuhan 430062, Peoples R China 2.Beijing Res Inst Uranium Geol, Beijing 100029, Peoples R China 3.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, Beijing 100085, Peoples R China 4.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 5.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai Inst Biol Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Peng, Jiangtao,Guo, Lu,Hu, Yong,et al. Maximum correntropy criterion based regression for multivariate calibration[J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS,2017,161:27-33. |
APA | Peng, Jiangtao,Guo, Lu,Hu, Yong,Rao, KaiFeng,&Xie, Qiwei.(2017).Maximum correntropy criterion based regression for multivariate calibration.CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS,161,27-33. |
MLA | Peng, Jiangtao,et al."Maximum correntropy criterion based regression for multivariate calibration".CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 161(2017):27-33. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论