发布时间：2014-10-20 来源：人大经济论坛

目 录 中文摘要...............................................................Ⅰ 英文摘要...............................................................II 目录...................................................................III 1. 绪论.................................................................1 1.1 小波分析.........................................................1 1.2 小波变换在化学计量学中的应用.....................................1 1.3 主成分回归.......................................................2 1.4 本研究的主要思路与方法...........................................3 2. 多组分同时测定的原理及实验方法.......................................4 2.1 计算分光光度法测定多组分的原理...................................4 2.2 实验方法与技术...................................................4 3. 算法基本原理.........................................................7 3.1 小波变换基本原理.................................................7 3.2 PCR数学原理.....................................................8 3.3 WT-PCR算法......................................................9 4. 实验部分............................................................11 4.1 实验仪器........................................................11 4.2 实验试剂........................................................11 4.3 实验方法........................................................11 5. 结果与讨论.........................................................13 5.1 吸收曲线与测定波长的选择.......................................13 5.2 样品稳定性分析.................................................14 5.3 训练样本的确定.................................................14 5.4 最佳小波基和截取尺度的选择.....................................16 5.5 主成分数的确定.................................................17 5.6 标准样品试验...................................................19 5.7 方法适用性试验.................................................19 5.8 加标回收试验...................................................20 5.9 未知样品预报...................................................21 6. 总结与展望..........................................................22 致谢...................................................................23 参考文献...............................................................24 附录MATLAB相关程序....................................................26 摘 要：在多组分样品的分光光度法测定中，吸收曲线常会发生不同程度的重叠,采用一般分光光度法难于定量每一组分，而近年来发展起来的小波变换（WT）已成为信息科学中的一个新兴研究领域，越来越多地应用于化学研究领域中各种复杂的、非线性的问题，也取得了很好效果。本文根据小波变换具有将信号分频的特点，采用db9小波在4尺度低频系数构造分析矩阵进行主成分回归(PCR)，预测结果优于原始数据全谱模型。利用小波变换与主成分回归相结合的一种多元校正算法对感冒液中对乙酰氨基酚、愈创木酚甘油醚、咖啡因和扑尔敏四组分体系进行了同时测定。加标回收率介于91.67-102.37%，结果基本满意。使用小波系数进行PCR建模，不仅可以有效地减小主成分向量残留噪声所引起的误差，而且较大地压缩了数据量，显著提高多元校正准确性，提高了预测精度。 关键词：小波变换；主成分回归；紫外分光光度法；多组分同时测定 The Study of Simultaneous Spectrophotometric Determination for Cough Syrup by Principal Component Regression Based on Wavelet Transform Abstract: In multi-component spectrophotometric determination， the absorption curve offen overlaps in varying degrees , It is difficult to quantitate each component using spectrophotometry generally, wavelet transform(WT)which is developed in recent years has become an emerging field of research in information science, and more and more used in the field of chemical research in a variety of complex, nonlinear problems, also achieved good results. In this paper, based on wavelet transform in accordance with the signal frequency characteristics, using wawelet db9 at level 4 to reconstruct a standard low-frequency coefficient for the original absorbance data to structure analysis matrix to rincipal component regression (PCR) regression analysis, forecasting results is better than the original entire spectrum model.Using a algorithm for multivariate calibration which was combining the WT and PCR technique applied to the simultaneous determination the Cough Syrup which has four components: acetaminophen, guuaifenesin, caffeine, p-aminophenol.the recovery ranged from 91.67% to 102.37% .the result is basically satisfied. Using wavelet coefficients to build PCR model, can not only effectively reduce the principal component vector of residual errors caused by noise , but also can greatly reduce the volume of data, significantly improve the accuracy of multivariate calibration to improve the prediction accuracy. Keywords: Wavelet transforrrmtion；PCR；UV spectrophotometry；Simultaneous determination of multiple components；