基于SVD的柴油机振动信号盲分离预处理

在利用独立分量分析对缸盖振动信号进行盲分离时,原始采样信号不满足独立分量分析的基本假设,而且缸盖振动信号信噪比较低,影响分离的速度和精度.采用小波阈值降噪的方法进行了降噪处理,提高了信噪比.采用奇异值分解的方法估计了缸盖振动的独立源数,并对缸盖振动信号进行了白化处理,为独立分量分析的应用建立了基础.     

Nonlinear Statistical Process Monitoring Based on Control Charts with Memory Effect and Kernel Independent Component Analysis

A novel nonlinear combination process monitoring method was proposed based on techniques with memory effect (multivariate exponentially weighted moving average (MEWMA)) and kernel independent component analysis (KICA). The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently developed statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of measurements and it is a two-phase algorithm: whitened kernel principal component analysis (KPCA) plus independent component analysis (ICA). The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear relationship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for long-term performance deterioration.     

State inspection for transmission lines based on independent component analysis

Monitoring transmission towers is of great importance to prevent severe thefts on them and ensure the reliability and safety of the power grid operation. Independent component analysis (ICA) is a method for finding underlying factors or components from multivariate statistical data based on dimension reduction methods, and it is applicable to extract the non-stationary signals. FastICA based on negentropy is presented to effectively extract and separate the vibration signals caused by human activity in this paper. A new method combined empirical mode decomposition (EMD) technique with the adaptive threshold method is applied to extract the vibration pulses, and suppress the interference signals. The practical tests demonstrate that the method proposed in the paper is effective in separating and extracting the vibration signals.     

智能车牌识别系统中消除图像干扰的方法

在智能车牌识别系统中,经过汽车图像的初分割,可从复杂的汽车及背景图像中分割出汽车图像,但复杂灰度图像经二值化处理后存在许多干扰白点.提出一种＂高斯滤波＂的方法去除这些白点,使二值化图像变得平滑、少毛刺,并具有较好的连通性.     

Robust digital audio watermarking scheme using blind source separation with global optimal property

The paper proposes a robust digital audio watermarking scheme using blind source separation(BSS) based on the global optimization of independency metric(IM),which is formulated as a generalized eigenvalue(GE) problem.Compared with traditional information-theoretical approaches used in digital audio watermarking,such as fast independent component analysis(FastICA),the proposed scheme has lower complexity without timeconsuming iteration steps used in FastICA.To make full use of the multiresolution characteris...     

An Image Retrieval Method Based on Color and Texture Features

The technique of image retrieval is widely used in science experiment, military affairs, public security,advertisement, family entertainment, library and so on. The existing algorithms are mostly based on the characteristics of color, texture, shape and space relationship. This paper introduced an image retrieval algorithm, which is based on the matching of weighted EMD(Earth Mover‘s Distance) distance and texture distance. EMD distance is the distance between the histograms of two images in HSV(Hue, Saturation, Value) color space, and texture distance is the L1 distance between the texture spectra of two images. The experimental results show that the retrieval rate can be increased obviously by using the proposed algorithm.     

Hepatic CT image query based on threshold-based classification scheme with gabor features

Hepatic computed tomography(CT) images with Gabor function were analyzed.Then a threshold-based classification scheme was proposed using Gabor features and proceeded with the retrieval of the hepatic CT images.In our experiments, a batch of hepatic CT images containing several types of CT findings was used and compared with the Zhao's image classification scheme, support vector machines(SVM) scheme and threshold-based scheme.     

Support vector regression based color image restoration in YUV color space

A support vector regression(SVR) based color image restoration algorithm is proposed.The test color images are firstly mapped into the YUV color space,and then SVR is applied to build up a theoretical model between the degraded images and the original one.Performance comparisons of the proposed algorithm versus traditional filtering algorithms are given.Experimental results show that the proposed algorithm has better performance than traditional filtering algorithms and has less computation time than iterat...     

沥青混合料图像多阈值分割方法

将基于遗传策略的多阈值分割法应用到沥青混合料图像分割中,解决了边缘检测法、单阈值法抗干扰性差、分割结果不能直接用于级配分析的难题。实验结果表明,该方法的分割精度优于边缘检测类和单阈值法,而且可将沥青混合料中的粗骨料、细骨料、纹理和空隙等组成部分分离出来,为后续的级配分析计算奠定基础,具有广阔的应用前景。     

基于独立分量分析的诱发电位信号提取方法

诱发电位（EP）信号在检测神经系统状态时有重要意义，但EP信号总是没在自发脑电波（EEG）信号中，因此，为利用EP信号诊断神经系统的损伤和病变，需要从二的混合信号中提出EP信号。独立分量分析（ICA）是一种新近发展起来的信号分离方法。本反ICA方法应用于EP信号的提取，并与传统的滤波方法进行了比较。计算模拟表明，采用ICA方法进行噪声分离的结果明显优于信号滤波方法。     

Image series segmentation and improved MC algorithm

A semiautomatic segmentation method based on active contour is proposed for computed tomography （CT） image series. First, to get initial contour, one image slice was segmented exactly by C-V method based on Mumford-Shah model. Next, the computer will segment the nearby slice automatically using the snake model one by one. During segmenting of image slices, former slice boundary, as next slice initial contour, may cross over next slice real boundary and never return to right position. To avoid contour skipping over, the distance variance between two slices is evaluated by an threshold, which decides whether to initiate again. Moreover, a new improved marching cubes （MC） algorithm based on 2D images series segmentation boundary is given for 3D image reconstruction. Compared with the standard method, the proposed algorithm reduces detecting time and needs less storing memory. The effectiveness and capabilities of the algorithm were illustrated by ,experimental results.     

独立分量分析在柴油机缸盖振动信号分离中的应用

采用独立分量分析的方法进行了柴油机缸盖振动信号分离的研究.建立了基于Fixed-pointICA算法的4135船用柴油机缸盖振动信号分析模型,分析了这些振动信号的性质.针对实际应用,对采集到的2路混合信号进行分离,得到了各独立分量的时域和频域分布.分离结果表明独立分量分析是一种行之有效的信号处理的新方法.     

基于HSI空间的模糊C均值彩色图像分割方法

给出了一种在HSI空间上基于模糊C均值的彩色图像分割方法．首先对每个像素根据H分量和I分量计算出4个隶属度,然后将其中的两个隶属度结合形成一个二雏特征矢量来表征像素的全部颜色特征,最后对二维矢量运用模糊C均值聚类算法得到最终的彩色图像分割结果．     

Incremental Supervised Subspace Learning for Face Recognition

Subspace learning algorithms have been well studied in face recognition. Among them, linear discriminant analysis (LDA) is one of the most widely used supervised subspace learning method. Due to the difficulty of designing an incremental solution of the eigen decomposition on the product of matrices, there is little work for computing LDA incrementally. To avoid this limitation, an incremental supervised subspace learning (ISSL) algorithm was proposed, which incrementally learns an adaptive subspace by optimizing the maximum margin criterion (MMC). With the dynamically added face images, ISSL can effectively constrain the computational cost. Feasibility of the new algorithm has been successfully tested on different face data sets.     

On-line Batch Process Monitoring and Diagnosing Based on Fisher Discriminant Analysis

Introduction Nowadays, it has been paying more attentionto the batch or semi-batch process which producedthe high added value and high quality products inchemical industry, such as polymer, pharmaceuti-cal and semiconductor industry.The aim of the batch process monitoring is tokeep the product quality uniform and consistentunder batch-to-batch process and meet specifica-tion limits. The direct approach is to monitor cru-cial product quality variables in batch process.However, quality variables…     

无地面控制点无人机影像的相对定向方法

针对无人机空中姿态不稳定造成影像相对定向精度较低的问题,提出了基于POS(positionand orientationsystem)数据生成无人机影像航带及组成立体像对的方法.并根据相对定向原理,将无人机的POS数 据作为相对定向的先验约束条件与误差方程一起进行平差,以重新构建代价函数,进行影像的相对定向.为验证 该方法的有效性,将其与常规的相对定向方法进行了对比实验.实验结果表明:将POS数据作为先验约束条件, 能够使相对定向精度提高10%以上,特别是在无人机影像畸变较大的情况下能获得较好的改善效果.      

图像分块下的隧道裂缝识别方法

针对隧道衬砌表面不均匀光照、渗水和噪声等强视觉干扰,设计了基于图像分块的隧道衬砌裂缝检测算法;根据中国西部地区的地理特征和隧道衬砌的外观病害,研制开发出一种快速、自动化的非接触式智能隧道结构物外观检测系统; 以非均匀光照下隧道图像数据集为研究对象,在图像分块的基础上提出一种适用于隧道裂缝特征提取的图像识别算法;研究了电子元件产生的噪声,并分析和总结了隧道衬砌的灾害特征;根据裂缝特征和分辨率将图像矩阵划分为适当数量的区域块,根据区域块的灰度特征将原始图像划分为目标背景区、目标病害区、病害背景区和其他区域,通过最大类间方差法和局部阈值法分割得到了隧道裂缝的粗图像,在此基础上进行了粗图像裂缝特征提取;对原始图像的每个区域块进行了对比度受限的自适应直方图均衡操作和局部阈值分割,得到了细节图像;将细节图像和粗图像的重叠区域设为理想裂缝二值化图像;结合隧道结构物外观检测系统对不同方向的裂缝图像进行了二值化试验,并通过隧道裂缝定位和投影法得到了隧道衬砌图像中裂缝的位置信息和方向。研究结果表明:提出的算法对隧道裂缝识别的准确值、召回率和F值可分别达90.34%、98.78%和94.37%,既可以保证隧道裂缝的完整性,也可以在非均匀光照下最大程度地保留目标裂缝的细节,可用于处理一般灰度图像的二值化问题。      

一种基于多项式拟合的UWB SAR目标鉴别稳健性评估方法

在超宽带合成孔径雷达（UWBSAR）目标鉴别性能评估中,稳健性是其中一项重要的性能指标,但关于此方面目前尚未有系统可行的评估方法提出．为此,文中提出了一种基于多项式拟合的稳健性评估方法．该方法提出了分离度一指标来衡量单信杂比情况下算法的鉴别性能,利用多项式模型实现对多信杂比情况下鉴别性能量化值的曲线拟合,提出了弹性指数的定义,并由拟合多项式得到对应的弹性指数方程,通过对弹性指数方程进行积分来实现对待评估鉴别算法稳健性的评估．基于所提出方法针对3种鉴别算法进行了评估试验,试验结果验证了方法的合理性．     

一种改进的InSAR干涉相位图估计方法

以联合子空间投影的干涉相位估计算法为基础,结合其应用稳健性问题,提出一种改进的In-SAR干涉相位图估计方法.该方法对联合自相关矩阵进行了加权处理.从幅度上抑制了干扰元素,提高了干涉相位图的精确性.仿真自然场景数据处理结果证明了改进算法的有效性和稳健性.     

基于多标记像素匹配的高分辨率遥感图像道路提取

针对高分辨率遥感图像道路提取方法存在提取不完整和误提取问题,提出一种基于多标记像素匹配的高分辨率遥感图像道路提取方法. 将待提取图像由RGB颜色空间转换到 Lab颜色空间,选取与照明强度弱相关的色相特征作为初始匹配项. 以矩形框的方式标记不同类型的道路,利用t 检验法剔除其匹配项的异常值,从而确定阈值来匹配道路像素点,利用局部纹理算子对匹配结果进行筛选. 利用道路区域的形态特征对匹配结果进行优化处理. 为验证所提方法的可行性和优越性,对不同传感器获取的高分辨遥感图像进行测试,与现有道路提取方法进行对比. 定性和定量精度评价结果表明,所提方法对不同类型道路的提取具有较高的精度.