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;