测试科学与仪器2016，Vol.7Issue(1)：24-29,6.DOI:10.3969/j.issn.1674-8042.2016.01.005
基于 JADE 的室内多组分污染气体混叠峰识别
Identification of indoor multi-component pollution gas aliasing peak based on JADE
摘要
Abstract
Monitoring indoor harmful gas can obtain the infrared spectra of mixed harmful gases.Since the absorption bands of mixed gases overlap and their qualitative and quantitative analyses are not easy,feature extraction method based on joint ap-proximative diagonalization of eigenmatrix (JADE)is proposed.By fully mining the hidden information of original data and an-alyzing higher-order statistics information of the data,each substance spectrum in the mixed gas can be accurately distinguish-ed.In addition,a multi-dimensional data quantitative analysis model of the extracted independent source is established by using support vector machine (SVM)based on regular theory.The experimental results show that the correlation coefficients of the components of mixed gases is above 0.999 1 by quantitative analysis,which verifies the accuracy of this feature extraction method.关键词
混叠峰识别/特征矩阵联合近似对角化/定量分析/支持向量机Key words
aliasing peak identification/joint approximative diagonalization of eigenmatrix (JADE)/quantitative analysis/sup-port vector machine (SVM)分类
信息技术与安全科学引用本文复制引用
王芳,李晋华..基于 JADE 的室内多组分污染气体混叠峰识别[J].测试科学与仪器,2016,7(1):24-29,6.基金项目
s:National Natural Science Foundation of China (No.61127015) （No.61127015）
