摘要
针对5种主次吸收峰严重交叠的红外混合气体定量分析问题,提出一种基于高阶累积量分析方法,该方法将重叠的吸收谱线映射到彼此相互分开的四阶累积量空间;在四阶累积量空间中提出一种基于正则理论和最小二乘相结合的支持向量机多维数据建模方法.在小样本下有效地提高了模型的准确度和收敛速度·实验结果表明,该方法使系统的引用误差小于4%,因而能满足外场使用的要求·
According to feature extraction of high order cumulant, a method is proposed to solve the quantitatively analyzing of five types of gas, where the primary and secondary absorbed peaks are seriously overlapped, The absorbed spectrogram is mapped to four-order cumulant space and detached from each other. A technique is presented based on support vector machine of regularization theory to construct multi-dimension model, and accuracy and iterated rate are improved in small scale samples. The result hints the referenced error is no more than 4 % , and satisfied with outfield demands.
出处
《光子学报》
EI
CAS
CSCD
北大核心
2006年第3期408-412,共5页
Acta Photonica Sinica
基金
国家自然科学基金(60276037)资助项目
关键词
气体分析
高阶累计量
支持向量机
特征提取
傅立叶红外光谱分析
Gas analyzing
High order cumulant
Support vector machine
Feature extraction
Fourierinfrared spectrum analyzing
