阿司匹林合成过程的在线拉曼光谱研究

利用在线拉曼光谱的方法,跟踪阿司匹林合成反应过程的实验.直接观测到反应过程中体系的拉曼光谱随时间的变化,用小波变换的方法去除光谱的本底之后, 又利用多波长线性回归的方法对实验数据进行实时的处理,得到了实验中各组分的相对浓度随时间的变化.     

小波变换用于二次微分交流示波计时电位信号中有用信息的提取

小波分析是８０年代发展起来的一种新的数学分支。由于小波变换具有许多其它的信号处理手段所不具备的优良特性，如正交性，可变的时－频分辨率和可调节的局部支持等，使它成为信号处理的一种强有力的工具。     

分析化学计量学中的新方法─—小波分析

小波分析在分析信号处理中具有诸多显著的优点。本文介绍了小波分析的一般描述，综述了化学计量学在的小波新方法，并展望了小波分析在分析化学计量学中的应用前景。     

小波分形分析重叠峰信号

用连续小波变换与分形理论相结合的小波分形峰位法对含噪重叠信号峰位置的提取进行了研究, 同时考察了信噪比和分离度对该法提取峰位置的影响; 结果表明 该法是一种提取含噪重叠信号中各单独峰峰位置的有效工具, 即使对于重叠程度和噪声干扰严重的信号也能得到较好的结果; 将其用于 Cd(Ⅱ )和 In(Ⅲ )重叠伏安信号的处理, 峰位置提取的相对误差小于± 1%; 该法具有准确、快捷、简便易行等特点, 发展前景广阔.     

Inequalities for Wavelet Frames

One of the fundamental problems in the study of wavelet frames is to find conditions on the wavelet function and the dilation and translation parameters so that the corresponding wavelet system forms a frame. In this article, we obtain some inequalities for a discrete wavelet system to be a frame. Our result improves known ones by Chui, Shi, and Chen.     

Numerical solutions to initial and boundary value problems for linear fractional partial differential equations

In this article, Haar wavelets have been employed to obtain solutions of boundary value problems for linear fractional partial differential equations. The differential equations are reduced to Sylvester matrix equations. The algorithm is novel in the sense that it effectively incorporates the aperiodic boundary conditions. Several examples with numerical simulations are provided to illustrate the simplicity and effectiveness of the method.     

Contrast enhancement for image by WNN and GA combining PSNR with information entropy

A new contrast enhancement algorithm for image is proposed combining genetic algorithm (GA) with wavelet neural network (WNN). In-complete Beta transform (IBT) is used to obtain non-linear gray transform curve so as to enhance global contrast for an image. GA determines optimal gray transform parameters. In order to avoid the expensive time for traditional contrast enhancement algorithms, which search optimal gray transform parameters in the whole parameters space, based on gray distribution of an image, a classification criterion is proposed. Contrast type for original image is determined by the new criterion. Parameters space is, respectively, determined according to different contrast types, which greatly shrink parameters space. Thus searching direction of GA is guided by the new parameter space. Considering the drawback of traditional histogram equalization that it reduces the information and enlarges noise and background blur in the processed image, a synthetic objective function is used as fitness function of GA combining peak signal-noise-ratio (PSNR) and information entropy. In order to calculate IBT in the whole image, WNN is used to approximate the IBT. In order to enhance the local contrast for image, discrete stationary wavelet transform (DSWT) is used to enhance detail in an image. Having implemented DSWT to an image, detail is enhanced by a non-linear operator in three high frequency sub-bands. The coefficients in the low frequency sub-bands are set as zero. Final enhanced image is obtained by adding the global enhanced image with the local enhanced image. Experimental results show that the new algorithm is able to well enhance the global and local contrast for image while keeping the noise and background blur from being greatly enlarged.     

Simultaneous Determination of Vitamin B Complex Using Wavelet Neural Network

A simultaneous determination of four components of B‐group vitamin, using a novel wavelet‐based neural network (WNN), combined with correlation coefficient and standard deviation approach for wavelength selection, was reported in this work. Eleven representative wavelength points were selected from each original UV spectrum, based on correlation coefficients and standard deviations of the observed data. A family of wavelet basic functions built from Morlet wavelet was adopted to improve the transfer quality of output data and solve the problems of training difficultly involved in neural networks. The predicted results, with fitting correlation coefficients (R = 0.9998–0.9999) and rooted mean squares errors (RMS = 0.0578–0.1478), are satisfactory.     

回归系数的岭型主相关估计及其优良性

本文研究了线性模型中的一种有偏估计,利用均方误差和残差平方和,得到了岭型主相关估计的一些性质,是对[1]中相关结果的推广.     

Speckle correlation fringes denoising using stationary wavelet transform. Application in the wavelet phase evaluation technique

This paper presents a stationary wavelet transform (SWT) method for speckle noise reduction in digital speckle pattern interferometry fringes. The main advantage of SWT is its translation invariance, which makes it important in statistical image processing applications. This method was used to denoise a simulated speckle fringe patterns, a good fidelity value was obtained. Applied to the wavelet phase evaluation, it has provided a phase distribution with a good accuracy.