CASIA OpenIR

Browse/Search Results:  1-10 of 15 Help

Selected(0)Clear Items/Page:    Sort:
A fast progressive spectrum denoising combined with partial least squares algorithm and its application in online Fourier transform infrared quantitative analysis 期刊论文
ANALYTICA CHIMICA ACTA, 2019, 卷号: 1074, 页码: 62-68
Authors:  Zhang, Genwei;  Peng, Silong;  Cao, Shuya;  Zhao, Jiang;  Xie, Qiong;  Han, Quanjie;  Wu, Yifan;  Huang, Qibin
Favorite  |  View/Download:14/0  |  Submit date:2019/07/11
Fourier transform infrared spectroscopy  Progressive spectrum denoising  Augmented Lagrange method  Partial least squares  Quantitative analysis  
An improved weighted multiplicative scatter correction algorithm with the use of variable selection: Application to near-infrared spectra 期刊论文
Chemometrics and Intelligent Laboratory Systems, 2019, 期号: 185, 页码: 114-121
Authors:  Yifan Wu;  Silong Peng;  Qiong Xie;  Quanjie Han;  Genwei Zhang;  Haigang Sun
View  |  Adobe PDF(1486Kb)  |  Favorite  |  View/Download:27/6  |  Submit date:2019/04/29
Multiplicative Scatter Correction  Weighted Least Squares  Variable Selection  Model Population Analysis  
Nonlinear least squares with local polynomial interpolation for quantitative analysis of IR spectra 期刊论文
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2018, 期号: 206, 页码: 147-153
Authors:  Yifan Wu;  Silong Peng;  Qiong Xie;  Pengcheng Xu
View  |  Adobe PDF(1404Kb)  |  Favorite  |  View/Download:21/5  |  Submit date:2019/04/29
Spectroscopy  Quantitative Analysis  Nonlinear Least Squares  Local Polynomial Interpolation  
A novel stacked regression algorithm based on slice transform for small sample size problem in spectroscopic analysis 会议论文
, Zhengzhou, China, July 20-22, 2018
Authors:  Yifan Wu;  Silong Peng;  Qiong Xie;  Quanjie Han
View  |  Adobe PDF(358Kb)  |  Favorite  |  View/Download:29/7  |  Submit date:2019/04/29
Small Sample Size Problem  Variable Selection  Stacked Regression  Slice Transform  
Iterative Reweighted Quantile Regression Using Augmented Lagrangian Optimization for Baseline Correction 会议论文
, 河南郑州, 2018年7月20至22
Authors:  Han QJ(韩权杰);  Peng SL(彭思龙);  Xie Q(谢琼);  Wu YF(吴义凡);  Zhang GW(张根伟)
View  |  Adobe PDF(552Kb)  |  Favorite  |  View/Download:20/8  |  Submit date:2019/04/24
Stochastic consensus of single-integrator multi-agent systems under relative state-dependent measurement noises and time delays 期刊论文
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2017, 卷号: 27, 期号: 5, 页码: 860-872
Authors:  Djaidja, S.;  Wu, Q. H.;  Cheng, L.
Favorite  |  View/Download:44/0  |  Submit date:2017/05/05
Single-integrator  Multi-agent Systems  Relative State-dependent Measurement Noises  Time Delays  Directed Topologies  
A lateralized top-down network for visuospatial attention and neglect 期刊论文
BRAIN IMAGING AND BEHAVIOR, 2016, 卷号: 10, 期号: 4, 页码: 1029-1037
Authors:  Wang, Jiaojian;  Tian, Yanghua;  Wang, Mengzhu;  Cao, Long;  Wu, Huawang;  Zhang, Yun;  Wang, Kai;  Jiang, Tianzi
Favorite  |  View/Download:104/0  |  Submit date:2017/02/14
Visuospatial Attention  Neglect  Superior Parietal Lobule  Visual Cortex  Tms  
一种数字出版资源语义增强描述系统及其方法 专利
专利类型: 发明, 专利号: CN201210566713.5, 申请日期: 2012-12-24, 公开日期: 2013-03-27
Inventors:  陈琳;  谢冰;  卢朋;  高一波;  武利娟;  代文;  宋江龙;  温伟娜
Favorite  |  View/Download:63/0  |  Submit date:2015/09/22
A simple probabilistic spiking neuron model with Hebbian learning rules 会议论文
International Joint Conference on Neural Networks (IJCNN), 2012
Authors:  Ting Wu;  Siyao Fu;  Long Cheng;  Rui Zheng;  Xiuqing Wang;  Xinkai Kuai;  Guosheng Yang
Favorite  |  View/Download:52/0  |  Submit date:2015/08/19
Recurrent Neural Network for Non-Smooth Convex Optimization Problems With Application to the Identification of Genetic Regulatory Networks 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2011, 卷号: 22, 期号: 5, 页码: 714-726
Authors:  Cheng, Long;  Hou, Zeng-Guang;  Lin, Yingzi;  Tan, Min;  Zhang, Wenjun Chris;  Wu, Fang-Xiang
Favorite  |  View/Download:51/0  |  Submit date:2015/08/12
Convex  Genetic Regulatory Network  Identification  Non-smooth Optimization Problem  Recurrent Neural Network