小波滤噪用于示波计时电位信号处理的研究

根据信号（Ｓ）和噪声（Ｎ）在小波变换下表现出的截然不同的性质,提出了一种新的滤噪方法,研究了噪音在不同细节的性质、滤噪阈值的确定及平滑与滤噪的特点。对不同Ｓ／Ｎ的示波计时电位信号进行了实验结果表明;小波滤噪在大大提高Ｓ／Ｎ的同时,信号强度基本不损失,优于传统的滤噪方法。     

一种新的小波滤波方法在化学谱图信号滤噪中的应用

仪器分析测定中，噪声的存在往往影响分析的准确度和仪器的检出限。小波变换多分辨分析的特性使得它成为一种很好的滤噪方法。基于小波分解后信号与噪声的小波系数随尺度变化规律不同的特性，提出了一种新的滤波滤方法-空域相关法，即通过不同尺度上相关系数模值与小波系数模模值的比较，达到滤波滤的目的。本文提出的方法具有无需人为选定无需人为选定滤噪阈值和小波函数、方法简单、失真度小等优点，可以大在提高信号的信噪比。模拟数据和ICP-AES实验数据证明了该方法的有效性。     

毛细管电脉在柱安培检测信号的小波滤噪研究

采用一种新的小波滤噪方法对毛细管电泳在柱安培检测信号进行了处理,研究了小波基的选择、噪音在不同细节中的特征以及噪音阈值的确定等,用此方法对酚类定量分析,结果信噪比、检测限和线性范围均有较大改善。     

毛细管电泳激光诱导荧光检测信号的小波滤噪

采用小波滤噪方法对毛细管电泳激光诱导荧光检测信号进行了处理，研究了小波变换中小波基的选择及噪声阈值的选择对滤噪的影响。结果表明，采用DB4小波基能有效消除毛细管电泳激光诱导荧光检测信号中存在的噪声，使信噪比得到较大改善。     

小波神经网络用于色谱数据的滤噪与压缩

介绍了小波神经网络（Ｗａｖｅｌｅｔ Ｎｅｕｒａｌ Ｎｅｔｗｏｒｋ）的结构和算法，并将其应用于色谱数据的滤噪与压缩。在小波神经网络中，采用了Ｂｕｂｂｌｅ母小波和一维搜索变步长共轭梯度优化方法。结果表明，小波神经网络将原始数据压缩至１：２０时，仍能得到很好的重建谱图。重建的色谱图不仅能保留原始的谱图特征而且有光滑滤噪的效果。对于色谱数据的存储与平衡滤噪具有重要意义。     

二进小波变换极大模法用于分析化学信号的滤噪

实验数据的滤噪在分析化学领域中具有重要的意义。小波变换技术具有很强的信号分离能力，容易把随机噪声从信号中分离出来，从而提高信号的信噪比。本文使用滤噪方法不同于传统离散小波变换方法，而是通过引入二进小波变换和李氏指数的概念，根据噪声与有用信号的极大模截然不同的特征，实现信号滤噪。实验数据的仿真结果研究也证明该方法的可行性。     

分析化学信号在多尺度空间的滤噪

从多分辨率分析出发，结合离散正交小波变换(DWT)的理论，通过对各尺度下未抽取前的小波系数进行非线性滤波处理，达到在保护信号边缘的同时，有效实现白噪声及脉冲噪声的滤除。实验数据仿真结果研究也证明了该方法的可行性。     

一种基于二进小波变换的自适应滤波方法

根据信号和噪声经小波变换后在不同尺度上有不同的特征，将相邻尺度二进小波变换值的相关量进行归一化处理并与小波变换值比较来判断信号与噪声，以噪声在各尺度的方差作为终止迭代的标准，提出了一种基于二进小波变换小波域选择噪声的自适应滤波方法。研究了模拟信号的去噪过程、半峰宽和信噪比对去噪结果的影响，并对模拟含噪信号和含噪毛细管电泳信号去噪前后的结果进行了比较。实验结果表明：由于该方法具有良好的自适应性和显著的滤波效果，必将得到广泛的应用。     

《分析化学中的小波分析技术》

小波变换的概念是由法国从事石油信号处理的工程师J．Morlet在1974年首先提出的并建立了反演公式。它解决了Fourier变换不能解决的许多困难问题，所以被誉为“数学显微镜”，具有分析发展史上里程碑式的意义。本书是分析科学现代方法丛书中的一册，是国内第一本介绍小波分析在分析化学中应用的图书。作者卢小泉教授自1994年始从事小波分析在分析化学中的应用研究，他在自己科研的基础上参阅了国内外大量的有关小波分析的文献后编著此书，书中内容具有很强的针对性和实用性。该书的出版能给分析化学工作者，特别是化学计量学工作者提供一些有价值的参考。     

《分析化学中的小波分析技术》

小波变换的概念是由法国从事石油信号处理的工程师J．Morlet在1974年首先提出的并建立了反演公式。它解决了Fourier变换不能解决的许多困难问题，所以被誉为“数学显微镜”，具有分析发展史上里程碑式的意义。本书是分析科学现代方法丛书中的一册，是国内第一本介绍小波分析在分析化学中应用的图书。作者卢小泉教授自1994年始从事小波分析在分析化学中的应用研究，他在自己科研的基础上参阅了国内外大量的有关小波分析的文献后编著此书，书中内容具有很强的针对性和实用性。该书的出版能给分析化学工作者，特别是化学计量学工作者提供一些有价值的参考。     

OWAVEC: a combination of wavelet analysis and an orthogonalization algorithm as a pre-processing step in multivariate calibration

In an spectroscopic context, when a calibration model based on partial least squares is developed to predict a response, it is often the case that a high percentage of variation in the data explained by the first latent variable is not accompanied by an equally high percentage of variation in the studied response. The addition of more components can slowly improve the calibration model, but with negative effects on the robustness and interpretability of the final model. To solve this problem, several pre-processing methods have been proposed to remove only a portion unrelated to the studied response from the spectral matrix.Moreover, the need for efficient compression methods is increasingly important due to the large size of the data currently collected. In this sense, discrete wavelet transform has proven that it can achieve good compression without losing relevant information when used on individual signals.This paper introduces a new pre-processing method, orthogonal wavelet correction (OWAVEC) that tries to lump together two important needs in multivariate calibration: signal correction and compression. The new method has been tested on a set of diesel fuels using viscosity as variable response, and its results have been compared not only with those obtained from original data but also with those provided by other correction methods. The first practical results are encouraging, as the method generates considerably better calibration models compared to the model developed from raw data and provides results as least so good as other orthogonal correction methods.     

小波变换用于示波信号中有用信息提取的研究

示波分析是近年来在我国发展起来的一个新的电化学分析研究领域［１～４］．它根据阴极射线示波器荧光屏上示波图及其变化进行分析测试,从原理上可以将其分为示波电位法和示波计时电位法;从测定方式上可以将其分为示波滴定和示波测定．关于示波电位法的一些理论问题（如...     

A method based on stochastic resonance for the detection of weak analytical signal

An effective method for detection of weak analytical signals with strong noise background is proposed based on the theory of stochastic resonance (SR). Compared with the conventional SR-based algorithms, the proposed algorithm is simplified by changing only one parameter to realize the weak signal detection. Simulation studies revealed that the method performs well in detection of analytical signals in very high level of noise background and is suitable for detecting signals with the different noise level by changing the parameter. Applications of the method to experimental weak signals of X-ray diffraction and Raman spectrum are also investigated. It is found that reliable results can be obtained.     

The kinetic energy operator in the subspaces of wavelet analysis

At any resolution level of wavelet expansions the physical observable of the kinetic energy is represented by an infinite matrix which is “canonically” chosen as the projection of the operator  − Δ/2 onto the subspace of the given resolution. It is shown, that this canonical choice is not optimal, as the regular grid of the basis set introduces an artificial consequence of its periodicity, and it is only a particular member of possible operator representations. We present an explicit method of preparing a near optimal kinetic energy matrix which leads to more appropriate results in numerical wavelet based calculations. This construction works even in those cases, where the usual definition is unusable (i.e., the derivative of the basis functions does not exist). It is also shown, that building an effective kinetic energy matrix is equivalent to the renormalization of the kinetic energy by a momentum dependent effective mass compensating for artificial periodicity effects.     

Predicting interspecies transmission of avian influenza virus based on wavelet packet decomposition

Using wavelet packet decomposition, the energy coefficients in the fifth level of viral protein sequences were achieved to predict interspecies transmission. Since avian-origin influenza viruses could have high sequence similarities with human-origin avian influenza virus and could have the phenotype of interspecies transmission, viral data should be filtered to prevent the misconduct of feature selection and false performance of predicting models. Considering the balance of data size, the empirical cut-off value 97% was used to screen avian-origin influenza virus with high sequence similarity. The excellent performances of cross validation show that the SVM model has the best capability of predicting transmission and evaluating the contribution of five amino acid factors. The robust model was finally used to evaluate the filtered data of avian-origin virus and the results confirmed that double check for ambiguous phenotype of avian-origin virus with high sequence similarity was necessary and part of them have the ability to across species barriers.     

A rapid fluorescence based method for the quantitative analysis of cell culture media photo-degradation

Cell culture media are very complex chemical mixtures that are one of the most important aspects in biopharmaceutical manufacturing. The complex composition of many media leads to materials that are inherently unstable and of particular concern, is media photo-damage which can adversely affect cell culture performance. This can be significant particularly with small scale transparent bioreactors and media containers are used for process development or research. Chromatographic and/or mass spectrometry based analyses are often time-consuming and expensive for routine high-throughput media analysis particularly during scale up or development processes.     

A feasibility study on the use of visible and short wavelengths in the near-infrared region for the non-destructive measurement of wine composition

The aim of this study was to explore the capability of spectroscopy in the visible (Vis) and short wavelength near-infrared (NIR) regions for the non-destructive measurement of wine composition in intact bottles. In this study we analysed a wide range of commercial wines obtained in Australia in different types of bottles (e.g. colours, diameters and heights), including different wine styles and varieties. Wine bottles were scanned in the Vis-NIR region (600–1,100 nm) in a monochromator instrument in transflectance mode. Principal component analysis (PCA) and partial least-squares (PLS) regression were used to interpret the spectra and develop calibrations for wine composition. Due to the relatively small number of samples available full cross-validation (leave-one-out) was used as validation. The coefficient of correlation in calibration and the standard error of cross-validation (SECV) were 0.67 (SECV: 0.48%), 0.83 (SECV: 4.01 mg L⁻¹), 0.70 (SECV: 28.6 mg L⁻¹) and 0.50 (SECV: 0.15) for alcohol content, total SO₂, free SO₂ and pH, respectively, in the set of wine samples analysed. These preliminary results showed that the assessment of wine composition by Vis and short wavelengths in the NIR is possible for either qualitative analysis (e.g. low-, medium- and high-quality grading), or for screening of composition during bottling and storage. Although low accuracy and precision were obtained for the chemical parameters routinely analysed in wine, calibration models for the chemical parameters were considered acceptable for screening purposes in terms of the standard errors obtained.     

基于化学计量学的通用化学数据采集处理系统

研制开发基于化学计量学的通用化学数据采集处理系统，该系统硬件采集部分，可与模拟信号输出的分析仪器或有RS－232接口的分析仪器联接进行数据采集，软件部分的数据处理基于化学计量学理论知识，相应数据处理方法，可从采集到数据中获取大量的信息。软件部分的信息管理包含了大量实验要素的归整、查询和统计等。     

A method to estimate the Leslie coefficients of liquid crystals based on MBBA data

A new effective approach for estimating the Leslie coefficients of liquid crystals based on MBBA data is presented. Literature values of the temperature-dependent Leslie viscosity coefficients of MBBA are used to fit with the analytical functions of Leslie coefficients based on the Imura and Okano theory, and a set of constants in these functions are determined. The same functions are then applied to two high birefringence liquid crystal mixtures, E7 and UCF-2, to extract their Leslie coefficients based on their order parameters. Using the extracted Leslie coefficients, the simulation results agree very well with the experimental data.