Estimating the time position of the pulse signal midpoint by a small number of samples in high-precision event timing

The interpolation method in event timing based on estimation of the time position of a monopulse signal by a small number (3 to 16) of samples is studied. It is shown that the estimates need to be corrected. An algorithm for constructing the corrective function using the reconstructed shape of the monopulse signal is proposed. The efficiency of the interpolation method is illustrated by the results of a computing experiment on time interval measurement.     

基于有序事件列表的高效复杂事件匹配算法

针对现有的复杂事件匹配处理方法存在的匹配代价高的问题,提出了一种利用事件缓冲区（有序事件列表）进行递归遍历的复杂事件匹配算法ReCEP。不同于现有方法利用自动机在事件流上进行匹配,该算法将复杂事件查询模式中的约束条件分解为不同类型,再在有序列表上对不同约束分别进行递归校验。首先,根据查询模式将相关事件实例按照事件类型进行缓存;其次,在有序列表上对事件实例执行查询过滤操作,并给出了一种基于递归遍历的算法来确定初始事件实例并且获取候选序列;最后,对候选序列的属性约束进行进一步的校验。基于股票交易模拟数据进行的实验测试和分析的结果表明,与当前主流的匹配方法 SASE和Siddhi相比,ReCEP算法能够有效地减少查询匹配的处理时间,总体性能上均更优,查询匹配效率提升了8.64%以上。可见,所提出的复杂事件匹配方法能够有效提高复杂事件匹配的效率。     

Simulation of linear continuous systems with distributed parameters

A new method for the simulation of distributed linear systems is presented. It is based on linear systems theory and digital signal processing rather than numerical mathematics. The essence of the method is the replacement of the Green's function for the continuous problem with the discretized Green's function of a discrete system. Its transfer function can be obtained by functional transformations and leads directly to a realizing structure which also incorporates initial and boundary conditions. The application of the method and its numerical efficiency over existing methods is demonstrated by an example.     

深度卷积神经网络下的图像风格迁移算法

针对图像风格迁移中出现的图像扭曲、内容细节丢失的问题,提出一种基于深度卷积神经网络的带有语义分割的图像风格迁移算法。定义内容图像损失和风格图像损失函数;对内容图像与风格图像分别进行语义分割,并将Matting算法作用在内容图像上,使用最小二乘惩罚函数来增强图片边缘真实性;进行图像的内容重建和风格重建生成新的图像。分析比较Neural Style改进方法、CNNMRF方法和带有语义分割的图像风格迁移方法生成的图像。实验结果和质量评估表明,70%带有语义分割的图像风格迁移方法生成的图像没有明显的图像扭曲,且内容细节完好。所以,该方法可以解决图像扭曲和细节丢失的问题,使内容丰富的图像可以得到精确的风格迁移。     

Digital representing of analog signals using event timing information

An approach to digitizing analog signals based on specific event timing is proposed. The events that have to be timed in this case with pico-second resolution and high precision are the signal and a sinusoidal reference function crossings. It is shown that the nonuniform sequences of the signal sample values obtained in this way carry the information needed for representing the respective analog signals in the digital domain. Software/hardware implementation of this method, based on high performance Event Timer A033-ET, is developed, evaluated and discussed.     

Logarithmic dyadic wavelet transform with its applications in edge detection and reconstruction

In this paper, based on the logarithmic image processing model and the dyadic wavelet transform (DWT), we introduce a logarithmic DWT (LDWT) that is a mathematical transform. It can be used in image edge detection, signal and image reconstruction. Comparative study of this proposed LDWT-based method is done with the edge detection Canny and Sobel methods using Pratt's Figure of Merit, and the comparative results show that the LDWT-based method is better and more robust in detecting low contrast edges than the other two methods. The gradient maps of images are detected by using the DWT- and LDWT-based methods, and the experimental results demonstrate that the gradient maps obtained by the LDWT-based method are more adequate and precisely located. Finally, we use the DWT- and LDWT-based methods to reconstruct one-dimensional signals and two-dimensional images, and the reconstruction results show that the LDWT-based reconstruction method is more effective.     

基于递归定量分析的视听脑电应用研究

视听觉整合的脑电信号研究丰富了脑认知领域的内容，但是现有的脑电信号分析方法大部分是基于线性的分析方法，同时对数据的信噪比要求较高。而基于相空间重构的排序递归图的递归定量分析方法对被测信号的噪声要求较低，并且是基于非线性的分析方法，为视听觉整合的研究提供了新的分析方法。设计不同视听刺激范式的实验，采集被试在不同刺激范式下的脑电数据。对预处理后的数据进行相空间重构，得到排序递归图。以递归率和确定性作为整合效果的分析参数。实验结果表明，该方法可以有效地从非线性角度分析视听觉整合效果，具有较高的准确性。     

Elastic bar transfer functions determination using one-point strain measurements

Measurements of impulsive forces and pressures by means of the elastic bar require that the effect of waves’ dispersion in the bar on the sensor's output signal be corrected. The correction problem can be solved using deconvolution techniques. For this purpose it is necessary to determine the elastic bar's transfer functions. In this paper, an experimental method of determining the elastic bar's transfer functions in form of formulas is described, which can be used to reconstruct the input waveform. The method is based on: one-point measurement of the elastic strain waves propagating inside the bar, the spectral analysis of these waves and making use of the general solution of the equation of movement of the bar in the frequency domain. The determined transfer functions of the bar are used for impulsive strain waveform reconstruction by means of deconvolution in the frequency domain, and for the validity check of the reconstruction. The application of this method to the reconstruction of impulsive force waveforms generated by the mechanical impact of bodies is presented.     

基于贝叶斯压缩感知的信号重构

本文提出了基于贝叶斯压缩感知的信号重构算法,将压缩感知理论应用于信号的压缩传输以及重构,该算法将压缩感知问题转化为线性回归问题,逐步推演出结果向量之间的迭代关系,最后通过迭代以得到原始信号的精确重构. 仿真说明了贝叶斯压缩感知在信号处理中的应用,结果表明该算法对一维和二维信号的压缩重构有很好的效果.     

SAR image reconstruction and autofocus by compressed sensing

A new SAR signal processing technique based on compressed sensing is proposed for autofocused image reconstruction on subsampled raw SAR data. It is shown that, if the residual phase error after INS/GPS corrected platform motion is captured in the signal model, then the optimal autofocused image formation can be formulated as a sparse reconstruction problem. To further improve image quality, the total variation of the reconstruction is used as a penalty term. In order to demonstrate the performance of the proposed technique in wide-band SAR systems, the measurements used in the reconstruction are formed by a new under-sampling pattern that can be easily implemented in practice by using slower rate A/D converters. Under a variety of metrics for the reconstruction quality, it is demonstrated that, even at high under-sampling ratios, the proposed technique provides reconstruction quality comparable to that obtained by the classical techniques which require full-band data without any under-sampling.     

改进的毫米波复数网络稀疏成像算法

针对基于压缩感知的重构方法耗时巨大的问题,从信号恢复的角度提出了一种基于深度学习方法的稀疏成像方案。首先,构建基于复数卷积的U-Net网络。其次,将欠采样信号输入网络得到满采样信号。最后,使用距离维脉压的二维匹配滤波算法重构出目标。实验建立在不同稀疏度和不同采样间隔下的欠采样仿真数据集中,并与传统和最近的信号处理方法进行对比。再使用实测数据进行验证,实验结果表明该算法在重构耗时以及图像平均梯度上具有更好的表现。     

基于事件语义特征的中文文本蕴含识别

为了强化文本蕴含系统深层语义分析与推理能力,该文提出了基于事件语义特征的中文文本蕴含识别方法。该方法基于事件标注语料生成事件图,将文本间的蕴含关系转化为事件图间的蕴含关系;利用最大公共子图的事件图相似度算法计算事件语义特征,与统计特征、词汇语义特征和句法特征一起使用支持向量机进行分类,得到初步实验结果,再经过基于事件语义规则集合的修正处理得到最后的识别结果。实验结果表明基于事件语义特征的中文文本蕴含识别方法可以更有效地对中文文本蕴含关系进行识别。     

Compression functions used in the algorithms for the estimation of signal arrival time under high-precision event timing

The possibilities are studied for improving the accuracy of the interpolation method for measuring the event occurrence time based on the digital processing of signals associated with the events. The problem of estimating the time of the analog signal arrival is formulated and solved as a problem of finding a fixed point of some contraction mapping. The compression function is constructed on the basis of spectral coefficients of a trigonometric series that approximates the shape of the analog signal. The accuracy potential of the interpolation measurement technique is illustrated by the results of computer simulation.     

Vague集在多传感器信息融合中的应用

采用Vague集来表达传感器的模糊测量信息,提出了一种基于Vague集的多传感器信息融合方法。该方法利用Vague值的记分函数,构造传感器测量值的有序加权平均对,再结合诱导有序加权平均算子确定传感器的权重,根据综合记分函数给出了信息融合方法。仿真实例验证了方法的有效性和具有较高的可信度。     

Untwisting a Projective Reconstruction

A method for upgrading a projective reconstruction to metric is presented. The method compares favourably to state of the art algorithms and has been found extremely reliable for both large and small reconstructions in a large number of experiments on real data. The notion of a twisted pair is generalized to the uncalibrated case. The reconstruction is first transformed by considering cheirality so that it does not contain any twisted pairs. It is argued that this is essential, since the method then proceeds by local perturbation. As is preferrable, we utilize a cost function that reflects the prior likelihood of calibration matrices well. It is shown that with any such cost function, there is little hope of untwisting a twisted pair by local perturbation. The results show that in practice it is most often sufficient to start with a reconstruction that is free from twisted pairs, provided that the minimized objective function is a geometrically meaningful quantity. When subjected to the common degeneracy of little or no rotation between the views, the proposed method still yields a very reasonable member of the family of possible solutions. Furthermore, the method is very fast and therefore suitable for the purpose of viewing reconstructions.     

Improvement of the accuracy of the time position estimation of the gravity center of an analog signal on the basis of discrete samples

The method of the interpolation measurement of the time instants of an event occurrence based on the estimation of the gravity center of a bell-shaped signal by spectral coefficients is presented. It is shown that the use of linear algorithms for estimating the spectral coefficients of a regression model allows for the picosecond accuracy of the measurements of the time intervals. The accuracy of the method is illustrated by computer simulation results.     

基于HHT变换的起动电动机特征信号时频分析

针对车辆起动电动机电气和机械故障发生时特征信号的时变不平稳特性,进行了时频域分析处理,提出了利用现代信号处理方法对故障信号提取特征向量的方法,主要对起动电动机的电枢和轴承故障进行诊断。在构建电机故障测试实验平台的基础上,利用破坏性实验构造了故障类型,测取了电枢电流和振动信号,分别采用小波分析理论和HHT变换对信号进行分析,通过分解再重构的方式将信号分解成了频率由高到低的不同分量,并获得了故障的特征频率,提取了特征向量。实验结果表明,基于HHT变换的现代信号处理方法在处理时变非平稳信号方面比小波分析理论更具有自适应性,更易识别。     

The Geometry and Matching of Lines and Curves Over Multiple Views

This paper describes the geometry of imaged curves in two and three views. Multi-view relationships are developed for lines, conics and non-algebraic curves. The new relationships focus on determining the plane of the curve in a projective reconstruction, and in particular using the homography induced by this plane for transfer from one image to another. It is shown that given the fundamental matrix between two views, and images of the curve in each view, then the plane of a conic may be determined up to a two fold ambiguity, but local curvature of a curve uniquely determines the plane. It is then shown that given the trifocal tensor between three views, this plane defines a homography map which may be used to transfer a conic or the curvature from two views to a third. Simple expressions are developed for the plane and homography in each case.A set of algorithms are then described for automatically matching individual line segments and curves between images. The algorithms use both photometric information and the multiple view geometric relationships. For image pairs the homography facilitates the computation of a neighbourhood cross-correlation based matching score for putative line/curve correspondences. For image triplets cross-correlation matching scores are used in conjunction with line/curve transfer based on the trifocal geometry to disambiguate matches. Algorithms are developed for both short and wide baselines. The algorithms are robust to deficiencies in the segment extraction and partial occlusion.Experimental results are given for image pairs and triplets, for varying motions between views, and for different scene types. The methods are applicable to line/curve matching in stereo and trinocular rigs, and as a starting point for line/curve matching through monocular image sequences.     

基于B样条曲线的断层离散数据平滑算法

通过二维断层图像进行三维对象重建是现今较为活跃的研究领域,而二维断层数据的质量将直接影响到三维重建的效果。提出了一种对医学断层离散数据在三维重建前进行预处理的方法,通过单层轮廓平面内平滑以及多层轮廓基于层间关系的B样条曲线拟合对原始数据进行了平滑处理,减少了重建后层与层之间的锯齿现象,使得在此基础上的三维重建效果得到了明显的改善。算法具有一定的通用性,同样适用于其它领域的数据处理。     

一种基于SVD和改进自适应算法的科氏流量计气体信号频率解算方法

频率解算是科氏流量计气体信号处理的首要任务。针对实际应用中气体信号信噪比低、频率波动大的特点,本文提出了一种基于SVD和改进自适应算法的科氏流量计气体信号频率解算方法。首先利用SVD对气体信号降噪并重构原信号,然后应用改进自适应算法处理重构信号,解算出频率。仿真及实验结果表明,本方法可以获得更快的收敛速度和更高的频率跟踪精度。