A novel blind deconvolution algorithm using single frequency bin

Former frequency-domain blind devolution algorithms need to consider a large number of frequency bins and recover the sources in different orders and with different amplitudes in each frequency bin,so they suffer from permutation and amplitude indeterminacy troubles. Based on sliding discrete Fourier transform,the presented deconvolution algorithm can directly recover time-domain sources from frequency-domain convolutive model using single frequency bin. It only needs to execute blind sepa-ration of instantaneous mixture once there are no permutation and amplitude indeterminacy troubles. Compared with former algorithms,the algorithm greatly reduces the computation cost as only one frequency bin is considered. Its good and robust per-formance is demonstrated by simulations when the signal-to-noise-ratio is high.     

用于通信信号非线性时域滤波的量子随机滤波器

针对通信信号的非线性时域滤波问题,研究了量子随机滤波器的原理和性能.将神经网络与非线性Schroedinger方程相结合,把方程的解作为信号时变的概率密度函数,进而实现滤波功能.研究发现,通过调整势场权系数的取值,可使滤波器具有明显不同的性能.根据此性质,构造了一种新的滤波算法,该算法可使滤波器在信号波形估计的非线性失真程度与它的抗噪能力之间进行折衷,这将大大推广量子随机滤波器的应用,例如,用于通信信号处理.仿真结果表明了量子随机滤波器的优越性能.     

一种基于小波的光谱反卷积方法

为消除测量光谱中狭缝宽度的影响，提出了一种基于小波的反卷积算法以获得问题的规整化解，该方法使用一维多尺度边缘重构技术．空域选择滤波算法被用来区分由信号产生的极值与由噪声产生的极值．实验中，对宽狭缝时测得的Na黄光2条特征语线进行反卷积处理，以相应狭缝宽度时测得的He-Ne光谱作为狭缝函数，并与较窄狭缝时测得的Na光谱作了比较．反卷积结果显示本方法可以极大地提高测量光谱的分辨率．     

基于 JADE 与小波分析的地震信号去噪算法研究

基于盲分离技术和小波分析,提出了消除地震信号噪声的一种新算法,这种算法将小波分析和盲信号分离技术有机结合,较好地发挥了消除地震信号随机噪声的作用;并通过应用到实际地震信号中,与其它去噪技术相比,此种去噪技术结果更理想。     

Research on ultrasonic detection of complex surfaces

INTRODUCTION Parts of complex surfaces have found wide ap-plications today in airplane,ship,automobile industry,medical science,etc.How to detect the internal de-fects of parts of complex surfaces efficiently and ac-curately is an important issue.Due to its special ad-vantages of high sensitivity,good detection,strong penetration ability,and harmlessness to human body,ultrasonic detection has become a most important method of Nondestructive Test(NDT).However,at present in China,to detec…     

基于小波变换的数字调制信号的特征提取

主要研究基于小波变换的数字调制信号的特征提取.和傅里叶变换不一样,小波变换是一个很好的时频分析工具.在实际中数字调制信号常常带有噪声(如白噪声等).首先对ASK、PSK、FSK信号进行小波分析,并对其特征进行提取(幅度、频率和相位等),其次对染噪的数字调制信号进行去噪处理,然后再进行小波分析比较.     

Identification of diesel front sound source based on continuous wavelet transform

Acoustic signals from diesel engines contain useful information but also include considerable noise components. To extract information for condition monitoring purposes, continuous wavelet transform (CWT) is used for the characterization of engine acoustics. This paper first reviews CWT characteristics represented by short duration transient signals. Wavelet selection and CWT are then implemented and wavelet transform is used to analyze the major sources of the engine front's exterior radiation sound. The research provides a reliable basis for engineering practice to reduce vehicle sound level. Comparison of the identification results of the measured acoustic signals with the identification results of the measured surface vibration showed good agreement.     

Identification of diesel front sound source based on continuous wavelet transform

Acoustic signals from diesel engines contain useful information but also include considerable noise components.To extract information for condition monitoring purposes, continuous wavelet transform (CWT) is used for the characterization of engine acoustics. This paper first reviews CWT characteristics represented by short duration transient signals.Wavelet selection and CWT are then implemented and wavelet transform is used to analyze the major sources of the engine front's exterior radiation sound. The research provides a reliable basis for engineering practice to reduce vehicle sound level.Comparison of the identification results of the measured acoustic signals with the identification results of the measured surface vibration showed good agreement.     

改进型小波阈值超声图像去噪方法

在D.L.Donoho提出的小波软、硬阈值去噪方法的基础上,提出了一种新的改进型半-软阈值方法,克服了经典小波阈值方法的缺点,能有效地改善图像的质量.通过Matlab对斑点超声图像进行去噪仿真,结果表明该方法优于软、硬阈值法,具有一定的应用价值.     

小波分析在钢板裂纹电涡流检测中的应用

在钢板的表面裂纹的在线检测中,经常利用电涡流检测技术,但是获得信号比较微弱,而且干扰严重;文章将小波变换引入到信号的处理中,对检测信号进行除噪,并加强其特征值,进而得到较好的检测信号。     

轴承滚子无损检测的信号采集与处理研究

采用激振方法,以声卡做为数据采集卡,应用MATLAB专用工具箱构建轴承滚子无损检测数据采集与处理系统,给出MATLAB环境中的程序设计和实现过程,并用实例证明该系统的有效性和实用性.     

小波分析在各领域中的应用及展望

小波分析在当今各个领域都得到了广泛的应用,它弥补了傅立叶变换及窗口傅立叶变换的不足,本文根据国内外本领域的研究情况,综合研究了信号处理、图像压缩、通信处理、信息安全、医学、化学、石油地质勘探、机械工程等各领域中的应用。     

A model for automatic identification of human pulse signals

This paper presents a quantitative method for automatic identification of human pulse signals. The idea is to start with the extraction of characteristic parameters and then to construct the recognition model based on Bayesian networks. To identify depth, frequency and rhythm, several parameters are proposed. To distinguish the strength and shape, which cannot be represented by one or several parameters and are hard to recognize, the main time-domain feature parameters are computed based on the feature points of the pulse signal. Then the extracted parameters are taken as the input and five models for automatic pulse signal identification are constructed based on Bayesian networks. Experimental results demonstrate that the method is feasible and effective in recognizing depth, frequency, rhythm, strength and shape of pulse signals, which can be expected to facilitate the modernization of pulse diagnosis.     

谈电路、信号分析与处理课程体系的调整与革新

本文阐述了电子、通信类专业中电路分析、信号与系统和数字信号处理课程体系和内容上的不足,提出了构建新的课程体系、整合和更新教学内容的基本思路及教学方式方法的改进措施.     

Modelling of ultrasonic motor with dead-zone based on Hammerstein model structure

The ultrasonic motor （USM） possesses heavy nonlinearities which vary with driving conditions and load-dependent characteristics such as the dead-zone. In this paper, an identification method for the rotary travelling-wave type ultrasonic motor （RTWUSM） with dead-zone is proposed based on a modified Hammerstein model structure. The driving voltage contributing effect on the nonlinearities of the RTWUSM was transformed to the change of dynamic parameters against the driving voltage. The dead-zone of the RTWUSM is identified based upon the above transformation. Experiment results showed good agreement between the output of the proposed model and actual measured output.     

Multifractal analysis of surface EMG signals for assessing muscle fatigue during static contractions

This study is aimed at assessing muscle fatigue during a static contraction using multifractal analysis and found that the surface electromyographic （SEMG） signals characterized multiffactality during a static contraction. By applying the method of direct determination ofthef（a） singularity spectrum, the area of the multifractal spectrum of the SEMG signals was computed. The results showed that the spectrum area significantly increased during muscle fatigue. Therefore the area could be used as an assessor of muscle fatigue. Compared with the median frequency （MDF）--the most popular indicator of muscle fatigue, the spectrum area presented here showed higher sensitivity during a static contraction. So the singularity spectrum area is considered to be a more effective indicator than the MDF for estimating muscle fatigue.     

电阻抗图象重建的新正则化方法

Image reconstruction in elecrical impedance tomography(EIT)is a highly ill-posed inverse problem,Regularization techniques must be used in order to solve the problem,In this paper,a new regularization method based on the spatial filtering theory is proposed.The new regularized reconstruction for EIT is independent of the estimation of impedance distribution,so it can be implemented more easily than the maxiumum a posteriori(MAP) method.The regularization level in our proposed method varies spatially so as to be suited to the correlation character of the object‘s impedance distribution.We implemented our regularization method with two dimensional computer simulations.The experimental results indicate that the quality of the reconstructed impedance images with the descibed regularization method based on spatial filtering theory is better than that with Tikhonov method.     

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.     

不同混沌源调制信号降低Boost型变换器电磁干扰水平研究

以Boost型DC／DC变换器为对象，研究在同一混沌调制模式下，不同混沌源对降低开关电源电磁干扰水平效果的影响。仿真结果表明：不同混沌源调制信号有不同的降低电磁干扰水平效果，Lorenz混沌源降低电磁干扰水平的效果较好。     

基于小波的图像增强算法在乳腺癌检测中的研究与应用

乳腺癌是现代女性最常见的恶性肿瘤之一,X光照片是一种在乳腺癌普查中广泛采用的检测手段。由于医学影像噪声大不清晰,检测结果往往不尽人意。本文以数字乳房X片图像为对象,研究了提高微钙化点的对比度的基于小波变换的图像增强算法。小波变换在时频域的多分辨率具有良好的空间域和频率域局部化特性。实验证明,基于小波多分辨率分析在抑制噪声的同时能对图像进行有效增强,提高图像的对比度,使钙化点的显示更为明显,提高了图像中病灶重要特征的可视化。基于小波的图像去噪和增强算法作为医学诊断的辅助手段有极其重要的意义。