小波变换及其在色谱重叠峰解析中的应用

本文介绍了小波分析的基本原理、计算方法及其在色谱重叠峰解析中的应用。显示了小波分析的特点，表明了小波分析用于重叠峰的解析与传统的方法相比具有其优越性。     

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。     

小波变换及其有色谱重叠峰解析中的应用

本文介绍了小波分析的基本原理、计算方法及其在色谱重叠峰解析中的应用。显示了小波分析的特点，表明了小波分析用于重叠峰的解析与传统的方法相比具有其优越性。     

基于有限脉冲响应滤波器的实时小波算法及其在色谱信号解析中的应用

对色谱信号进行正确、实时地解析是利用色谱仪器系统进行过程检测的关键技术。小波分析方法能对色谱信号进行有效解析,但实时性一直是制约该方法在色谱信号处理中广泛应用的一个瓶颈。多分辨率分析与重构算法(MALLAT)是小波分析的一种快速算法,但是该算法的实时性仍然需要进一步提高。针对这一问题,以MALLAT算法原理为基础,利用在分解重组过程中两组滤波器系数之间的关系提出了一种基于有限脉冲响应滤波器的实时小波分析算法。仿真结果表明,与经典的MALLAT小波快速算法相比,该算法在保持信号有效分解与重构的基础上,运行耗时明显缩短,实时性得到较大提高。     

小波分析和人工神经网络方法用于重叠色谱峰的解析

将神经网络与小波分析相结合,提出一种利用小波变换提取重叠色谱峰信息,再用人工神经网络解析的方法,为色谱峰重叠难于分开的物质的测定提供一种方法,提高了色谱分析的准确度,并将此方法应用于高效液相色谱中,建立了混合体系中3.4-二甲酚和2.5-二甲酚同时测定的新化学计量学方法.     

连续样条小波变换用于分解重叠峰的研究

以B-样条小波为分析小波，提出了用于分析化学重叠信号解析的新方法——连续样条小波变换，结果表明：连续样条小波变换应用于分析化学信号的处理，能使峰变窄同时还能提高信号的信噪比，是一种新型有效的重叠信号解析方法，能从含噪声重叠信号中直接得到重叠峰的峰数目及其相应的峰位置。     

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。     

小波变换与分析化学信号处理

介绍了小波变换的基本理论并对小波变换的常用算法和应用进行了评述。由于小波变换的时2频局部化性质, 使其成为信号处理的强有力工具。在分析化学领域中, 小波变换在流动注射分析、伏安分析、高效液相色谱、红外光谱、质谱、核磁共振谱、可见-紫外光谱、光声光谱、扩展X-射线吸收精细结构(EXAFS) 谱等分析化学信号的平滑滤噪、数据压缩、重叠信号解析等方面都有成功的应用。     

一种新型交替迭代算法用于农药GC-MS信号快速分析

化学计量学算法为重叠GC-MS信号解析提供了有效手段. 免疫算法(IAs)可根据标准样品的信号(色谱或质谱)对重叠GC-MS信号进行解析并得到重叠信号中各组分的信息. 但是标样信号与实际测量信号之间的差别会造成解析结果出现偏差. 针对标样信号与测量信号不一致的问题, 作者提出了一种交替迭代算法用于重叠GC-MS测量信号的直接解析. 该方法在不提供标样信号的情况下可以解析出组分的质谱和色谱信息. 计算过程中, 采用随机产生的质谱作为初始输入, 利用最小二乘和IA算法交替计算质谱和色谱, 直到满足终止条件. 采用所建立的方法对40种组分的农药混合物进行了分析, 使用快速升温程序在10 min保留时间内得到了全部组分的色谱和质谱信息.     

小波包分析-减法聚类-RBF网络同时测定痕量铁、锰

提出一种解析分光光度吲时测定数据的小波色分析-减法聚类-RBF刚络新方法。该方法用小波包分析处理吸收光潜数据,滤除信号中的噪声;采用基于山峰函数的减法聚类算法,按照自适应聚类的结果构成预测各未知样的校正集,实现校准模型的优化;由此,使RBFM络在对未知样预测时能更有效地提取光潜数据中的特征信息,提高预测结果的准确性把该算法用于模拟汽油中铁、锰合成样预测,计算表明,该方法可以显著降低测定结果的相对误差,预测结果令人满意。     

基于小波变换平滑主成分分析

小波变换具有很强的信号分离能力,很容易把随机噪音从信号中分离出来,从而提高信号的信噪比。本文把小波变换引入到因子分析中,提出了基于小波变换平滑主成分分析,该算法既保留普通主成分分析的正交分解,又具备了小波变换的信号分离能力。模拟数据和实验数据的结果表明,该算法具有从低信噪比的数据中提取出有用信息,并提高信号的信噪比。迭代目标变换因子分析处理实验数据的结果表明,基于小波变换平滑主成分分析的处理结果优     

Quantification of components in overlapping peaks from capillary electrophoresis by using continues wavelet transform method

The application of continues wavelet transform (CWT) for resolving overlapping peaks from capillary electrophoresis (CE) is described. Overlapping peaks can be resolved easily by transforming experimental signals into their wavelet coefficients. The proposed method was applied for the determination of benzoic acid and salicylic acid in overlapping peaks from CE. The composition of the two acids in Zuguangsan, a traditional Chinese patent medicine, was determined. The quantification results are satisfactory. CWT has been shown to be a practicable approach for resolving overlapping peaks and for quantitative determining coeluted compounds in overlapping peaks from CE. The quantification results obtained from CWT were compared with those obtained from numerical differentiation method. CWT has been shown prior to numerical differentiation method for processing experimental signals which contain noise.     

Wavelet Derivative: Application in Multicomponent Analysis of Electrochemical Signals

The wavelet derivative was developed for resolving overlapped signals in electrochemical analysis. It has been shown that the wavelet derivative could be used as an effective tool in resolution enhancement of the electrochemical signals. Since signal‐to‐noise ratio (SNR) does not degrade significantly at high order derivatives, the wavelet derivative is much better than the conventional numerical derivative in resolving practical signals with low SNR, particularly in the case when the overlapped degree of complex is high and high order derivatives are required for the further resolution enhancement. In this article, applications of the wavelet derivative in the voltammetric determination of small mounts of substances in the presence of large mounts of potentially interfering species are presented, and the advantages of this technique are discussed as well.     

基于分形理论分辨重叠峰的新算法

将分形理论用于仪器分析信号的解析,提出一种面向分析谱图中重叠信号处理的分形分辨算法.通过对信号进行分形分析,采用分形维数可有效地反映信号的特征,准确地得到谱峰个数和位置的信息,避免人为判断的误差,实现重叠复合信号的分辨.实验表明,这种新的重叠谱峰分辨法能用于光谱、电化学、色谱等仪器分析数据的处理     

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.     

A two-dimensional immune algorithm for resolution of overlapping two-way chromatograms

A two-dimensional immune algorithm is proposed for resolving the multicomponent overlapping two-way data matrices. The method is a development of the one-dimensional immune algorithm proposed elsewhere. When the inner product of vectors is expanded to the similar operation on matrices, the 1D immune algorithm can be expanded to the 2D algorithm which is suitable for the analysis of two-way data matrices. Both simulated and experimental two-way data sets were investigated by the method, and the results prove that the 2D immune algorithm is an effective tool for resolving the overlapping two-way signals. The effect of noise on the recoveries is also discussed.     

A two-dimensional immune algorithm for resolution of overlapping two-way chromatograms

A two-dimensional immune algorithm is proposed for resolving the multicomponent overlapping two-way data matrices. The method is a development of the one-dimensional immune algorithm proposed elsewhere. When the inner product of vectors is expanded to the similar operation on matrices, the 1D immune algorithm can be expanded to the 2D algorithm which is suitable for the analysis of two-way data matrices. Both simulated and experimental two-way data sets were investigated by the method, and the results prove that the 2D immune algorithm is an effective tool for resolving the overlapping two-way signals. The effect of noise on the recoveries is also discussed.     

基于小波理论的化学谱图数据自适应滤波方法研究

运用小波理论,利用噪声与真实信号小波变换极大模性态之间的显著差异,提出了一类新的化学谱图数据自适应滤波算法,从根本上突破了现有算法均依据信噪频率特性进行滤波的传统模式.经大量色谱谱图数据处理试验证明,这种算法具有无需设置初始参数,消除人为误差因素对分析计算结果的影响,信噪分离性能好及峰位和峰高保持不变等一系列优点,其鲁棒性、自适应性和谱峰保真度完全符合仪器分析信号处理的要求.     

在线小波变换用于伏安分析仪的研制

将在线小波变换应用于伏安信号的在线处理,研制了具有小波变换功能的伏安分析仪。该系统利用在线小波变换对采集到所数据进行实时处理,具有控制灵活,分辨率高,数据处理方便等特点。通过对低浓度Ｃｙ＾２＋和Ｆｅ＾３＋混合样品的阶梯斜坡扫描伏安珠滤噪及定性,定量分析,结果表明可获得满意的分析结果。