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。     

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。     

免疫算法用于多组分二维色谱数据的解析

通过对免疫系统抗体对抗原消除作用及其记忆功能的模拟,提出了解析二维数据矩阵的新方法。采用模拟的EMG公式作为抗体输入,对二维信号逐行进行迭代消除,从重叠峰中提取单一组分的色谱信息和光谱信息。通过对二维色谱数据的解析,结果表明,该方法可方便地用于多组分重叠二维色谱的解析。     

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。     

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.     

正交投影用于多波长色谱重叠峰分析

 将正交投影分辨 (OPR)技术用于多波长色谱重叠峰分辨 ,当色谱峰中最大重叠度小于或等于波长数时 ,用这一方法能从多波长色谱重叠峰中获得完全真解。基于双波长色谱分析 ,提出了一种新的色谱重叠峰中背景校正、组分数和纯组分信号区确定以及各组分重叠情况的分析方法 ,即双波长特征信息分析 (DWCI)。该法被成功的用于三组分双峰和双组分单峰重叠色谱的分析。     

完全重叠色谱峰的二维微分色谱解析算法

利用完全重叠的色谱峰中同时消失的两组分的浓度变化速率差异，通过二维数据微分色谱法获取被掩盖组份的近似光谱，以解析完全重叠的色谱体系，将该法应用于维生素Ｃ和菸酸两组份完全重叠的二维色谱之分辨，结果令人满意，分辨光谱与标准光谱重合甚好。     

模差渐进投影法解析重叠色谱峰

提出了一种鉴别重叠色谱峰类型的化学计量学方法——模差渐进投影(MDEP)法。该方法利用二维色谱数据中相邻两个色谱流出点的光谱矢量模的和与该两个矢量和的模之差,建立模差-时间(dm-t)曲线判断非纯色谱峰的纯组分区,同时判定第二组分色谱流出点和倒数第二组分色谱结束点。分别以纯组分区的光谱矢量建立正交阵对该色谱峰进行投影运算,得到投影后转换色谱。该转换色谱消除了纯组分区所对应化合物的色谱和光谱信息。对转换色谱重复上述操作至整个色谱峰的模差-时间曲线均为0时终止,得到重叠色谱峰各组分的色谱流出点和结束点。利用上述结果,采用不包含待测组分光谱信息的该重叠峰二维色谱数据建立正交矩阵对该色谱峰进行投影运算,获得待测组分的相似色谱图。通过比对分析即可得到该组分在重叠色谱峰中的光谱和色谱信息。依次操作,即可获得重叠色谱峰中各组分的光谱和色谱信息。采用模差渐近投影法对4组分模拟重叠二维色谱峰及杜香挥发油GC-MS的重叠色谱峰进行了解析,方法简便、结果准确。     

二维小波变换与子窗口因子分析法结合用于含噪声HPLC-DAD数据的解析

将二维小波变换与子窗口因子分析法相结合,用于模拟的高噪声HPLC-DAD数据的解析.首先应用二维小波变换滤除噪声,然后采用子窗口因子分析法解析重叠峰.结果表明,信噪比为10的高噪声基本被滤除掉.     

一种新型的信号拟合方法--免疫算法

通过对免疫系统免疫机制的模拟,提出了一种新型的信号拟合算法。该算法根据所提供的标样信息对重叠分析化学信号进行拟合,从重叠信号中提取单一组分的信息,从而实现了多组分混合信号的解析。对模拟信号的实验信号的处理结果表明,该方法可方便地用于多组分重叠色谱信号的解析。     

小波包分析用于重叠分析化学信号的处理

对小波包分析的算法进行了改进,并将此算法成功地应用于多组分重叠色谱信号的解析.结果表明,本文提出的算法解决了MRSD算法的不足,更适合处理分析化学信号,用于重叠信号的解析时不需重构(逆变换),简化了数据处理步骤,加快了数据解析速度,具有较强的解析能力.对于重叠色谱信号的解析,小波包分析比小波分析具有更强的解析能力.     

Resolution of multicomponent NMR signals using wavelet compression and immune algorithm

A novel algorithm for fast resolution of multicomponent overlapping nuclear magnetic resonance (NMR) spectrum using the wavelet compression and the immune algorithm (IA) is proposed. Taking advantage of the linear property of the wavelet transform (WT), the overlapping NMR spectrum (antigen) can be compressed by WT before it is input into the immune network, the antibodies are also compressed to the same scheme. After extraction of the compressed information of each component, the resolved NMR spectra can be restored by the WT reconstruction. It was proven that the result is almost the same with the result from an IA, but the calculation speed is much faster.     

一种新型的信号拟合方法─—免疫算法

通过对免疫系统免疫机制的模拟,提出了一种新型的信号拟合算法。该算法根据所提供的标样信息对重叠分析化学信号进行拟合,从重叠信号中提取单一组分的信息,从而实现了多组分混合信号的解析。对模拟信号和实验信号的处理结果表明,该方法可方便地用于多组分重叠色谱信号的解析。     

An improved transmutation method for quantitative determination of the components in multicomponent overlapping chromatograms

An improved method is proposed for the quantitative determination of multicomponent overlapping chromatograms based on a known transmutation method. To overcome the main limitation of the transmutation method caused by the oscillation generated in the transmutation process, two techniques—wavelet transform smoothing and the cubic spline interpolation for reducing data points—were adopted, and a new criterion was also developed. By using the proposed algorithm, the oscillation can be suppressed effectively, and quantitative determination of the components in both the simulated and experimental overlapping chromatograms is successfully obtained.     

An immune algorithm for resolution of multicomponent overlapping chromatograms

A novel immune algorithm for resolution and quantitative determination of the components in overlapping chromatograms was proposed by imitating biological immune systems. The algorithm takes an overlapping chromatogram as its input and subtracts the chromatograms of standard samples from the input by iteration of a network. When the residual does not change, the network will converge and chromatographic information of the components in overlapping chromatogram will be obtained. Both simulated and experimental data sets were investigated by the method. Results showed that both resolved results and recoveries of quantitative determination are satisfactory. Comparing with conventional least-square method, the immune algorithm is fast in calculation.     

An immune algorithm for resolution of multicomponent overlapping chromatograms

A novel immune algorithm for resolution and quantitative determination of the components in overlapping chromatograms was proposed by imitating biological immune systems. The algorithm takes an overlapping chromatogram as its input and subtracts the chromatograms of standard samples from the input by iteration of a network. When the residual does not change, the network will converge and chromatographic information of the components in overlapping chromatogram will be obtained. Both simulated and experimental data sets were investigated by the method. Results showed that both resolved results and recoveries of quantitative determination are satisfactory. Comparing with conventional least-square method, the immune algorithm is fast in calculation.