{"title":"用小波填充变换和偏最小二乘法定量测定具有重叠紫外光谱的多分量。","authors":"Ling Gao, Shouxin Ren","doi":"10.1155/JAMMC/2006/86989","DOIUrl":null,"url":null,"abstract":"<p><p>This paper presented a novel method named wavelet packet transform-based partial least squares method (WPTPLS) for simultaneous spectrophotometric determination of alpha-naphthylamine, p-nitroaniline, and benzidine. Wavelet packet representations of signals provided a local time-frequency description and separation ability between information and noise. The quality of the noise removal can be improved by using best-basis algorithm and thresholding operation. Partial least squares (PLS) method uses both the response and concentration information to enhance its ability of prediction. In this case, by optimization, wavelet function and decomposition level for WPTPLS method were selected as Db16 and 3, respectively. The relative standard errors of prediction (RSEP) for all components with WPTPLS and PLS were 2.23% and 2.71%, respectively. Experimental results showed WPTPLS method to be successful and better than PLS.</p>","PeriodicalId":15248,"journal":{"name":"Journal of Automated Methods & Management in Chemistry","volume":"2006 ","pages":"86989"},"PeriodicalIF":0.0000,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/JAMMC/2006/86989","citationCount":"0","resultStr":"{\"title\":\"Quantitative determination of the multicomponents with overlapping ultraviolet spectra using wavelet-packed transform and partial least squares.\",\"authors\":\"Ling Gao, Shouxin Ren\",\"doi\":\"10.1155/JAMMC/2006/86989\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This paper presented a novel method named wavelet packet transform-based partial least squares method (WPTPLS) for simultaneous spectrophotometric determination of alpha-naphthylamine, p-nitroaniline, and benzidine. Wavelet packet representations of signals provided a local time-frequency description and separation ability between information and noise. The quality of the noise removal can be improved by using best-basis algorithm and thresholding operation. Partial least squares (PLS) method uses both the response and concentration information to enhance its ability of prediction. In this case, by optimization, wavelet function and decomposition level for WPTPLS method were selected as Db16 and 3, respectively. The relative standard errors of prediction (RSEP) for all components with WPTPLS and PLS were 2.23% and 2.71%, respectively. Experimental results showed WPTPLS method to be successful and better than PLS.</p>\",\"PeriodicalId\":15248,\"journal\":{\"name\":\"Journal of Automated Methods & Management in Chemistry\",\"volume\":\"2006 \",\"pages\":\"86989\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/JAMMC/2006/86989\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Automated Methods & Management in Chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/JAMMC/2006/86989\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Automated Methods & Management in Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/JAMMC/2006/86989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantitative determination of the multicomponents with overlapping ultraviolet spectra using wavelet-packed transform and partial least squares.
This paper presented a novel method named wavelet packet transform-based partial least squares method (WPTPLS) for simultaneous spectrophotometric determination of alpha-naphthylamine, p-nitroaniline, and benzidine. Wavelet packet representations of signals provided a local time-frequency description and separation ability between information and noise. The quality of the noise removal can be improved by using best-basis algorithm and thresholding operation. Partial least squares (PLS) method uses both the response and concentration information to enhance its ability of prediction. In this case, by optimization, wavelet function and decomposition level for WPTPLS method were selected as Db16 and 3, respectively. The relative standard errors of prediction (RSEP) for all components with WPTPLS and PLS were 2.23% and 2.71%, respectively. Experimental results showed WPTPLS method to be successful and better than PLS.