首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于支持向量机的非线性荧光光谱的识别
引用本文:李素梅,韩应哲,张延炘,常胜江,申金媛.基于支持向量机的非线性荧光光谱的识别[J].光学学报,2006,26(1):47-151.
作者姓名:李素梅  韩应哲  张延炘  常胜江  申金媛
作者单位:南开大学信息技术科学学院教育部光电信息技术重点实验室,天津,300071
基金项目:中国科学院资助项目 , 天津市自然科学基金 , 天津市科技攻关项目 , 高等学校博士学科点专项科研项目 , 南开大学校科研和教改项目
摘    要:提出将支持向量机网络应用于含不同浓度杂质气体的非线性荧光光谱的识别。由于原始光谱数据的光谱通道数目很大,首先用小波变换去噪压缩,然后采用主成分分析方法对光谱信息进行连续两次的特征提取。在保持原光谱数据主要信息基本不变的情况下,将数据维数由3979压缩到514(小波变换)并提取9个主成分。这样,不仅减少了网络的输入维数,而且加快了网络的训练速度。实验结果表明,无论对训练样本还是未学习过的测试样本,其正确识别率均可达到100%。网络的训练和测试速度较快,可以更有效地应用于大气杂质气体的实时监测。

关 键 词:光谱学  非线性荧光光谱  支持向量机  小波变换  主成分分析
文章编号:0253-2239(2006)01-0147-5
收稿时间:2005-03-17
修稿时间:2005-06-07

Recognition of Nonlinear Fluorescence Spectrum of Support Vector Machine Networks
Li Sumei,Han Yingzhe,Zhang Yanxin,Chang Shengjiang,Shen Jinyuan.Recognition of Nonlinear Fluorescence Spectrum of Support Vector Machine Networks[J].Acta Optica Sinica,2006,26(1):47-151.
Authors:Li Sumei  Han Yingzhe  Zhang Yanxin  Chang Shengjiang  Shen Jinyuan
Institution:Key Lab of Opto-electronics Information Technical Science, EMC, College of Information Technical Science, Nankai University, Tianjin 300071
Abstract:That the support vector machine network is applied to recognize the nonlinear fluorescence spectrum of impurities of different concentrations in air is proposed.Because the number of spectrum channel of the original spectrum data is large,it is cleaned up and compressed through wavelet trausform firstly,and then the principal component analysis(PCA) is used to extract the character information twice in series.It not only ensures the character of original nonlinear fluorescence spectrum,but also compresses the data number the nonlinear fluorescence spectrum from 3979 to 514,and extracts 9 principal components,which reduces the number of the input vector and improves the training speed of the network.The simulation results show that the correct recognition rates for both training spectrum samples and unlearned test spectrum samples reach 100%.So,the training and testing speed is fast enough to monitor the atmospherical impurity in air in real time.
Keywords:spectroscopy  nonlinear fluorescence spectrum  support vector machine  wavelet transform  principal component analysis
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号