小波变换-主成分回归分光光度法同时测定邻苯二酚、间苯二酚和对苯二酚三组分

根据小波变换具有将信号分频的特点,本文提出了将小波变换与主成分回归(PCR)相结合的一种多元校正算法。该法能更有效地去除噪声,提取有用信息,并将其用于分析邻苯二酚、间苯二酚、对苯二酚三组分体系。实验结果表明,本法比直接用主成分回归处理效果好,得到的平均相对误差从2．24％降低到1．19％。     

离散小波变换-支持向量回归方法同时测定苯酚、苯胺和苯甲酸

在波长范围200～400nm测定苯酚、苯胺和苯甲酸混合液的吸收光谱,用离散小波变换（DWT）对光谱数据进行处理,再用支持向量回归SVR方法进行建模,建立了离散小波变换一支持向量回归方法（DWT—SVR）。方法用于模拟样品和污染水样中苯酚、苯胺和苯甲酸的同时测定,结果满意。     

Daubechies小波主成分回归法机理及算法研究

将小波变换与主成分回归相结合,提出一种新型多元校正算法---小波基主成分回归法。理论分析和仿真实验表明,该法可更有效地去除噪声,提取有用信息。将其用于氯霉素及甲硝唑实际药物体系分析,与主成分回归法(PCR)相比,得到的回收率总平均相对误差由1.70%下降到0.90%。此外,通过将统计判据和小波多尺度分析相结合,发展了一种新的因子数判定方法。理论和实验研究表明,该法比传统因子数判定法具有更高的可靠性。     

连续小波变换-独立成分回归算法及其在多组分分析中的应用

采用连续小波变换（CWT）对光谱数据进行处理，用独立成分分析（ICA）进行特征提取，再用回归分析方法对被测组分进行测定，建立了连续小波变换一独立成分回归（CWT-ICR）方法。方法用于肉样品中水分、脂肪和蛋白质多组分的同时测定，所得结果与化学法测得结果相符。     

小波变换用于植物激素重叠色谱峰中组分的定量分析

根据小波变换将信号按频率大小分解的性质，作者提出了一种用小波变换直接提取重叠色谱峰中单一组分信息的方法，并将其应用于植物激素混和体系重叠峰的解析与定量分析。结果表明：单组分的色谱信号经小波变换分解后仍能保持原有的线性关系，用小波变换从重叠信号中提取的单一组分信息也具有良好的线性关系。     

小波变换用于色谱重叠峰的解析

利用小波变换的时频局部化性质，通过对色谱重叠峰信号小波变换后的某些频率段进行放大，使重叠谱峰得到了分离，并将此方法用于苯和甲苯二组分色谱体系的定量分析，重叠峰中各组分均得到了良好的线性关系及令人满意的定量分析。本文还讨论了不同小波基、分解的次数及放大系数在解析结果的影响。     

小波包变换潜变量回归分辨重叠的紫外光谱

采用小波包变换潜变量回归(WPLVR)方法,同时测定联苯、苯酚和邻苯二酚。该法结合小波包变换和潜变量回归改进除噪质量。通过最佳化,选择了小波函数及小波包分解水平(L)。编制了两个程序PWPLVR和PFTLVR进行WPLVR和付立叶变换潜变量回归(FTLVR)法计算。试验结果表明WPLVR法是成功的且优于FTLVR法。     

小波变换用于重叠色谱峰组分信息的提取

提出了一个小波变换用于提取重叠色谱中组分信息的理论公式，并将它应用于三组分和五组分重叠色谱实验数据的解析。结果表明：在定定分离度范围内，当相邻色谱峰峰宽相近时，根据此公式的计算结果，可以将各组分的信息从重叠色谱峰信号中提取出来。洒工作对小波变换用于重叠峰的解析具有重要意义。     

小波包变换潜变量回归同时测定三组分混合物

采用小波包变换潜变量回归 (WPLVR)方法 ,同时测定水杨酸甲酯(MSA)、邻苯二甲酸二丁酯 (DBP)和邻苯二甲酸氢钾 (PHP)。该法结合小波包变换和潜变量回归改进除噪质量。通过最佳化 ,选择了小波函数及小波包分解水平 (L)。编制了两个程序 (PWPLVR)和 (PFTLVR)进行WPLVR和付立叶变换潜变量回归 (FTLVR)法计算。实验结果表明WPLVR法是成功的且优于FTLVR法。     

小波潜变量回归和广义回归神经网络同时测定三组分混合物

本文采用小波潜变量回归（WLVR）方法，同时测定重叠的光谱信号。结合小波阈值法和主组分分析（PCA）改进除噪质量。八个误差判据用于推断因子数目。潜变量由小波处理过的信号投影到正交基矢量而获得。广义回归神经网络（GRNN）被应用于多组分同时测定。依据算法原理编制了三个程序（PWMRA、PWLVR和PGRNN）执行有关计算。三个方法（WLVR、LVR（潜变量回归）和GRNN）同时测定三组分混合物，获得满意的结果。     

Simultaneous quantitative analysis of overlapping spectrophotometric signals using wavelet multiresolution analysis and partial least squares

The mathematical bases and program algorithms of discrete wavelet transform (DWT), multiresolution and Mallat’s pyramid algorithm were described. The multiresolution analysis (MRA) based on Daubechies orthogonal wavelet basis was studied as a tool for removing noise and irrelevant information from spectrophotometric spectra. After wavelet MRA pre-treatment, eight error functions were calculated for deducing the number of factors. A partial least squares based on wavelet MRA (WPLS) method was developed to perform simultaneous spectrophotometric determination of Fe(II) and Fe(III) with overlapping peaks. Data reduction was performed using wavelet MRA and principal component analysis (PCA) algorithm. Two programs, SPWMRA and SPWPLS, were designed to perform wavelet MRA and simultaneous multicomponent determination. Experimental results showed the WPLS method to be successful even where there was severe overlap of spectra.     

Comparison of methods for the processing of voltammetric electronic tongues data

We are making a numerical comparison of various preprocessing strategies for dealing with data from voltammetric electronic tongues in order to reduce the high dimensionality of the response matrices. Different modelling tools are presented and briefly described. We then compare combinations of four preprocessing strategies (principal component analysis, fast Fourier transform, discrete wavelet transform, voltammogram-windowed slicing integral) with four modelling alternatives (principal component regression, partial least squares regression, multi-way partial least squares regression, artificial neural networks) by employing data from a voltammetric bioelectronic tongue, an array formed by enzyme-modified biosensors and applied to the discrimination and quantification of phenolic compounds.

基于小波系数的近红外光谱局部建模方法与应用研究

局部建模方法使用与预测样本相似的样本建立模型,可解决光谱响应与浓度之间的非线性问题,扩大模型的适用范围,提高预测准确度。采用小波变换进行数据压缩并利用小波系数之间的欧氏距离作为光谱相似性的判据,实现了近红外光谱定量分析的局部建模方法,避免了样本之间的依赖性。将所建立的方法用于烟草样品中氯含量的测定,100次重复计算得到的预测集均方根误差(RMSEP)平均值为0.0665,标准偏差(σ)为0.0045,优于全局建模和基于主成分的局部建模方法。     

Resolution of overlapping signals in spectrometry using a wavelet packet transform and an Elman recurrent neural network

A novel method named a wavelet packet transform based Elman recurrent neural network (WPTERNN) was proposed for the simultaneous UV–visible spectrometric determination of Cu(II), Cd(II) and Zn(II). This method combined wavelet packet denoising with an Elman recurrent neural network. A wavelet packet transform was applied to perform data compression, to extract relevant information, and to eliminate noise and collinearity. An Elman recurrent network was applied for nonlinear multivariate calibration. In this case, using trials, the kind of wavelet function, the decomposition level, and the number of hidden nodes for the WPTERNN method were selected as Daubechies 14, 3, and 8, respectively. A program (PWPTERNN) was designed that could perform the simultaneous determination of Cu(II), Cd(II) and Zn(II). The relative standard errors of prediction (RSEP) obtained for all components using WPTERNN, a Elman recurrent neural network (ERNN), partial least squares (PLS), principal component regression (PCR), Fourier transform based PCR (FTPCR), and multivariate linear regression (MLR) were compared. Experimental results demonstrated that the WPTERRN method was successful even where there was severe overlap of spectra. The results obtained from an additional test case also demonstrated that the WPTERNN method performed very well. Figure The part of WP coefficients obtained by wavelet packet transforms     

化学计量学在电分析化学中的新进展

评述了化学计量学的各种方法,如主成分分析、偏最小二乘、小波分析、人工神经网络等在电分析化学中的进展,主要介绍了这些方法在电分析化学中的应用,并展望了化学计量学在电分析化学中的应用前景。     

Multivariate calibration of spectral data using dual-domain regression analysis

To date, few efforts have been made to take simultaneous advantage of the local nature of spectral data in both the time and frequency domains in a single regression model. We describe here the use of a novel chemometrics algorithm using the wavelet transform. We call the algorithm dual-domain regression, as the regression step defines a weighted model in the time-domain based on the contributions of parallel, frequency-domain models made from wavelet coefficients reflecting different scales. In principle, any regression method can be used, and implementation of the algorithm using partial least squares regression and principal component regression are reported here. The performance of the models produced from the algorithm is generally superior to that of regular partial least squares (PLS) or principal component regression (PCR) models applied to data restricted to a single domain. Dual-domain PLS and PCR algorithms are applied to near infrared (NIR) spectral datasets of Cargill corn samples and sets of spectra collected on batch chemical reactions run in different reactors to illustrate the improved robustness of the modeling.     

化学计量学在过程分析中的应用及进展

评述了化学计量学方法在生产过程分析中各个方面 ,如过程优化、过程模拟、仪器及仪器校正、过程监测等方面的应用 ,并展望了化学计量学在过程分析中的应用前景     

Fractional-continuous wavelet transforms and ultra-performance liquid chromatography for the multicomponent analysis of a ternary mixture containing thiamine, pyridoxine, and lidocaine in ampules

New chemometric approaches based on the application of partial least squares (PLS) and principal component regression (PCR) algorithms with fractional wavelet transform (FWT) and continuous wavelet transform (CWT) are proposed for the spectrophotometric multicomponent determination of thiamine hydrochloride (B1), pyridoxine hydrochloride (B6), and lidocaine hydrochloride (LID) in ampules without any separation step. In this study PLS and PCR techniques were applied to the raw spectral data, FWT-coefficients, and FWT-CWT-coefficients. These calibration models were labeled as Raw-PLS and Raw-PCR, FWT-PLS and FWT-PCR, and FWT-CWT-PLS and FWT-CWT-PCR, respectively. A new ultra-performance liquid chromatographic (UPLC) method was developed for the comparison of the results obtained by applying the chemometric calibration methods. Chromatographic separation and determination of B1, B6, and LID in ampules were performed on an Acquity UPLC BEH C18 column (50x2.1 mm id, 1.7 pm particle size) using gradient elution with a mobile phase consisting of methanol and 0.01 M HCI at a constant flow rate of 0.6 mL/min. These combined chemometric calibrations and UPLC were validated by analyzing various ternary mixtures, B1, B6, and LID. The proposed chemometric approaches (signal processing-multivariate calibrations) and UPLC method were applied to the quantitative multicomponent analysis of marketed ampules containing the vitamins B1 and B6 with LID.