Discriminant analysis of multivariate time series: Application to diagnosis based on ECG signals

In analysing ECG data, the main aim is to differentiate between the signal patterns of healthy subjects and those of individuals with specific heart conditions. We propose an approach for classifying multivariate ECG signals based on discriminant and wavelet analyses. For this purpose we use multiple-scale wavelet variances and wavelet correlations to distinguish between the patterns of multivariate ECG signals based on the variability of the individual components of each ECG signal and on the relationships between every pair of these components. Using the results of other ECG classification studies in the literature as references, we demonstrate that our approach applied to 12-lead ECG signals from a particular database compares favourably. We also demonstrate with real and synthetic ECG data that our approach to classifying multivariate time series out-performs other well-known approaches for classifying multivariate time series.     

Measurement and analysis of fluorescent whitening agent content in soybean milk based on image techniques

This paper presents a method for measuring and quantitatively analyzing the fluorescent whitening agent in soybean milk based on image techniques. After collecting the fluorescent images of the soybean milk samples, the top seven wavelet moment invariants are selected according to the sample training and experimental comparison. Then calculate the standard templates of the 49 classes of calibration samples with different fluorescent whitening agent content ranging from 0.02 mg/ml to 0.5 mg/ml. The minimum distance method is carried out to match the testing sample with the calibration template, which realizes the quantitative analysis. To verify the effectiveness of the presented method, the prediction experiment is carried out. Results show that the absolute errors are within 0.005 mg/ml and the relative errors are within 5%, which means this method can measure the fluorescent whitening agent in soybean milk. This research presents a new approach for detecting the illegal fluorescence additive in food production.     

On the statistical decorrelation of the 2D discrete wavelet transform coefficients of a wide sense stationary bivariate random process

We present a second order statistical analysis of the 2D Discrete Wavelet Transform (2D DWT) coefficients. The input images are considered as wide sense bivariate random processes. We derive closed form expressions for the wavelet coefficientsʼ correlation functions in all possible scenarios: inter-scale and inter-band, inter-scale and intra-band, intra-scale and inter-band and intra-scale and intra-band. The particularization of the input process to the White Gaussian Noise (WGN) case is considered as well. A special attention is paid to the asymptotical analysis obtained by considering an infinite number of decomposition levels. Simulation results are also reported, confirming the theoretical results obtained. The equations derived, and especially the inter-scale and intra-band dependency of the 2D DWT coefficients, are useful for the design of different signal processing systems as for example image denoising algorithms. We show how to apply our theoretical results for designing state of the art denoising systems which exploit the 2D DWT.     

基于二维小波变换的爆堆矿岩边缘检测

根据爆堆图像灰度分布的特点,并结合小波变换应用于边缘检测的基本原理,采用能够检测局部突变能力的B样条小波用于爆堆岩石的边缘检测。通过推导,给出B样条小波滤波器,并根据滤波器设计出了基于二维小波边缘检测算法。在小波边缘分割中自主设计了自适应阈值检测算法,该算法能很好地去除图像的噪声,并保留了图像的边缘。     

小波域高斯混合模型方差估计近红外降噪方法

针对抑制近红外光谱噪声与保留光谱信号细节的矛盾,提出一种基于噪声方差估计的小波域降噪方法.该法对光谱信号小波域高频系数建立了两状态高斯混合模型,用EM算法估计模型系数,推证模型对噪声方差准确估计特性,将估计得到的噪声方差建立了阈值降噪模型.实验建立黄酒近红外光谱快速预测酒精度偏最小二乘模型,对比分析Penalty阈值、...     

几种常用遥感影像融合方法分析及初步试验

本文对目前在影像融合过程中最常用的融合方法进行了简单归纳和介绍,并运用Brovey变换、主成分变换、小波变换、IHS变换等融合方法对某一试验区SPOT5卫星的全色和多光谱数据进行融合处理,并对融合结果进行了定量分析对比,得出对于实验数据来说最适合的融合方法.     

基于小波域TS-MRF模型的监督图像分割方法

定义在单一空间分辨率上的树结构马尔可夫场(Tree-Structured Markov Random Field,TS-MRF)模型能够表达图像的分层结构信息,但难以描述图像的非平稳性,针对该问题,提出小波域的TS-MRF图像建模方法-WTS-MRF模型,按照图像分类层次树的结构形式,该模型将一系列的MRF嵌套定义在多...     

Identification of rod dynamics under influence of Active Magnetic Bearing

The purpose of this paper is to apply the wavelet transform algorithm to identify the magnetic damping and magnetic stiffness coefficients of the drive rod with which a set of 4-pole Active Magnetic Bearing (AMB) is equipped. By taking advantage of time–frequency analysis feature, the ridge curve of rod free response after wavelet transformation can be extracted to find the natural frequency of the rod/AMB system. In other words, due to the influence of magnetized field by the AMB, the stiffness of the rod dynamics is not linear any more and can be estimated from the curve of the amplitude versus frequency by wavelet transformation. On the other hand, the nonlinear damping coefficients can be estimated from the derivative of amplitude versus amplitude by wavelet transformation of rod free vibration. It is found that the nonlinear magnetic damping coefficients are up to 2nd-order in polynomial and the stiffness coefficient is mainly of 3rd-order respectively. In addition, the identified 2nd-order damping coefficient is negative and hence implies that under specific rod displacement and speed, the dynamic of the rod/AMB system in axial direction is unstable.     

基于小波和侧抑制网络的红外图像增强算法

针对红外图像存在的对比度差、信噪比低等问题,提出了一种基于小波和侧抑制网络的红外图像对比度增强算法.该算法首先利用小波变换法对图像进行小波分解,然后分别采用优化局部阈值和侧抑制网络法对分解后的高频系数和低频系数进行处理,最后进行小波重构,即得到增强后的图像.实验表明:该算法能够在实现图像增强的同时,较好地抑制图像噪声,...