A blind source separation algorithm based on negentropy and signal noise ratio

A novel blind source separation (BSS) algorithm based on the combination of negentropy and signal noise ratio (SNR) is presented to solve the deficiency of the traditional independent component analysis (ICA) algorithm after the introduction of the principle and algorithm of ICA. The main formulas in the novel algorithm are elaborated and the idiographic steps of the algorithm are given. Then the computer simulation is used to test the performance of this algorithm. Both the traditional FastICA algorithm and the novel ICA algorithm are applied to separate mixed signal data. Experiment results show the novel method has a better performance in separating signals than the traditional FastICA algorithm based on negentropy. The novel algorithm could estimate the source signals from the mixed signals more precisely.     

Study of engine noise based on independent component analysis

Independent component analysis was applied to analyze the acoustic signals from diesel engine. First the basic prin-ciple of independent component analysis (ICA) was reviewed. Diesel engine acoustic signal was decomposed into several inde-pendent components (ICs); Fourier transform and continuous wavelet transform (CWT) were applied to analyze the independent components. Different noise sources of the diesel engine were separated, based on the characteristics of different component in time-frequency domain.     

基于独立分量分析的MMSE多用户检测

将独立分量分析，即ICA应用于DS-CDMA系统的多用户检测中，提出了基于ICA后处理的最小均方误差MMSE多用户检测方法。该方法用MMSE检测的输出来初始化独立分量分析的迭代．既利用了信源的独立性，又充分利用了已知扩频码的信息，从而提高了多用户检测器的性能。仿真结果表明：此方法在高信噪比的情况下，误码性能得到了较大改善。     

基于小波变换的地震信号去噪方法研究

提高信噪比是地震信号数字处理的主要任务．研究了几种常用的小波去噪方法在地震信号中去除随机噪声的应用,分析了各自的特点,并改进了算法．通过MATLAB的仿真结果表明,小波变换的去噪效果明显优于传统的Fourier变换方法．     

A new computing multivariate spectral analysis method based on wavelet transform

This paper proposes a new algorithm for multivariate calibration named Principal Component Regression Based on Wavelet (PCRW) which combines wavelet decomposition technique with the factor analysis method for establishing a duplicate denoising mechanism. A practical example in spectral analysis of a typical multicomponent pharmaceutical system was used to verify the effectiveness of the algorithm. It was shown that PCRW produced fewer prediction errors than those obtained by using PCR. Project (39870940) supported by NSFC.     

BSS algorithm for dependent signals using Cook s nonGaussianity measure

Based on the generalization of the central limit theorem(CLT) to special dependent variables, this paper shows that maximization of the nonGaussianity(NG) measure can separate the statistically dependent source signals, and the novel NG measure is given by Cook‘s Euclidean distance using the Chebyshev-Hermite series expansion. Then, a novel blind source separation (BSS) algorithm for linear mixed signals is proposed using Cook‘s NG measure, which makes it possible to separate statistically dependent source ...     

Investigation on the automatic parameters extraction of pulse signals based on wavelet transform

This paper analyses a key problem in the quantification of pulse diagnosis. Due to the subjectivity and fuzziness of pulse diagnosis,quantitative methods are needed. To extract the parameters of pulse signals,the prerequisite is to detect the corners of pulse signals correctly. Up to now,the pulse parameters are mostly acquired by marking the pulse corners manually,which is an obstacle to modernize pulse diagnosis. Therefore,a new automatic parameters extraction approach for pulse signals using wavelet transform is presented. The results testified that the method we proposed is feasible and effective and can detect corners of pulse signals accurately,which can be expected to facilitate the modernization of pulse diagnosis.     

Motion classification of EMG signals based on wavelet packet transform and LS-SVMs ensemble

This paper presents an effective method for motion classification using the surface electromyographic (sEMG) signal collected from the forearm. Given the nonlinear and time-varying nature of EMG signal, the wavelet packet transform (WPT) is introduced to extract time-frequency joint information. Then the multi-class classifier based on the least squares support vector machine (LS-SVM) is constructed and verified in the various motion classification tasks. The results of contrastive experiments show that different motions can be identified with high accuracy by the presented method. Furthermore, compared with other classifiers with different features, the performance indicates the potential of the SVM techniques combined with WPT in motion classification.     

一种基于小波变换的多尺度图像配准算法

在研究传统Harris角点检测算法的基础上,结合小波变换的多分辨率特性,提出一种基于小波变换边缘检测与Harris角点检测的多尺度图像配准算法。该算法保持了Harris角点检测算法在图像旋转、缩放或灰度变化时角点提取效果依然良好的优点,改进了其对噪声敏感且不具有尺度不变性的缺点,在不同尺度上有较高稳定性与匹配精准度,抗噪性较强。     

小波变换在植被格局分析中的应用

本文通过野外实地观测,利用小波理论尝试性地分析了1000m样带上植被总盖度在不同尺度下的分布特征。通过不同尺度下小波变换映像值的分析,解决了植被格局研究中在不同尺度下同时进行规模、强度、纹理分析这一久而未决的难题,发现了植被格局规模在不同尺度下的变化符合分形性质的特点。     

基于小波方法的超分辨率图像重建

提出了一种基于小波变换理论的超分辨率重建算法,即利用小波变换得到图像的高频和低频子带,结合非线性外推技术对高频子带进行处理,在增加高频子带信息量的同时进行迭代改进,并采用小波阈值方法进行去噪处理.实验结果表明：该算法能够克服以往插值算法的不足,如高频损失、细节模糊等,能很好地提高图像的峰值信噪比,是图像重建的一种有效方法.     

Watermarking on 3D mesh based on spherical wavelet transform

INTRODUCTIONTherapidgrowthofdigitalmediaoverInternetprovideseverybodywiththefacilityofeasyaccess,copy,editanddistributionofdigitalcontentssuchaselectronicdocuments,images,soundsandvideos.Thereisurgentdemandfortechniquestoprotectthecopyrightoftheoriginaldigitaldataandtopreventunauthorizedduplicationortampering.Digitalwatermarkingordatahidingisonesolutionforthecopyrightprotectionofdigitaldata.Digitalwatermarkingisaprocessbywhichauser-specifiedsignal(watermark)ishiddenorembeddedintoanothersi…     

Watermarking on 3D mesh based on spherical wavelet transform

In this paper we propose a robust watermarking algorithm for 3D mesh. The algorithm is based on spherical wavelet transform. Our basic idea is to decompose the original mesh into a series of details at different scales by using spherical wavelet transform; the watermark is then embedded into the different levels of details. The embedding process includes: global sphere parameterization, spherical uniform sampling, spherical wavelet forward transform, embedding watermark, spherical wavelet inverse transform, and at last resampling the mesh watermarked to recover the topological connectivity of the original model. Experiments showed that our algorithm can improve the capacity of the watermark and the robustness of watermarking against attacks.     

基于小波变换的电力滤波器信号调整与分析

本文介绍了小波变换原理,通过对有源电力滤波器的通道信号分解与重构、对谐波进行处理,采用MATLAB工具的函数模块对其通道信号作了仿真分析,结果表明小波变换的多分辨率特性能有效修正仪器通道谐波畸变波及频谱,对进一步实现滤除谐波问题有指导意义。     

Very low bit-rate video coding based on wavelet transform

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一种新的基于小波变换的基音检测算法

1IntroductionPitch periodis ani mportant parameterinthe analys-is and synthesis of speech signals.Pitch period infor-mation is used in various applications such as(1)speaker identification and verification,(2)pitch syn-chronous speech analysis and synthesis,(3)linguisticand phonetic knowledge acquisition and(4)voice dis-ease diagnostics.However the task of esti mating thepitchis very difficult since(1)the human vocal tract isvery flexible andits characteristics varyfrompersontoperson,(2)the pi…     

基于主分量分析的数字水印

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基于小波变换的低比特率图像编码研究

运用小波变换理论,结合人类视觉系统特性,提出一种基于SPIHT算法的低比特率图像压缩的改进算法.实验证明,该算法在平滑图像的压缩中有较好效果,在低比特率压缩下减少了Gibbs现象,边缘模糊现象得到改善.     

基于小波变换的DEM多尺度分析模型的研究

介绍了小波、离散小波变换和多尺度分辨分析的基本思想及利用小波分析对空间数据进行多尺度表达的三个模型．利用小波分析的方法和模型简化DEM数据并对DEM数据进行多尺度表达．实验结果表明，这些模型和方法对DEM的多尺度表达效果非常明显．