室内定位中非视距的识别和抑制算法研究综述

针对存在非视距(non-line-of-sight, NLOS)的室内定位算法进行研究.首先描述室内定位中的常用技术和算法(航迹推算、指纹识别定位、邻近探测、极点定位、三角定位、多边定位、质心定位),概括其原理、优缺点和适用场景;其次,通过仿真测试说明研究NLOS识别和抑制的必要性;再次,分别介绍NLOS识别和NLOS抑制的几类算法, NLOS识别算法包括统计学方法、几何关系法、机器学习法、信道特征提取法和虚点密度识别法, NLOS抑制算法包括模糊理论法、引入平衡参数法、几何关系法、小波去噪法、机器学习类算法、凸优化类算法、残差类算法、最小二乘类算法和多维缩放类算法;最后,对全文进行总结并指出NLOS室内定位亟待解决的问题.     

图像轮廓提取方法研究

对现有的轮廓提取现状进行分析,把主要的轮廓提取方法划分为先验知识法、数学形态法、基于梯度的方法、水平集方法、活动轮廓模型方法、以及神经动力学方法六大类,并研究这些方法的主要特点。对轮廓提取方法研究进行展望,提出神经动力学方法是轮廓提取方法的发展方向。     

人脸画像合成研究的综述与对比分析

人脸画像合成通常是在给定一些训练画像-照片的前提下,将一张输入的人脸照片转换为画像的过程.目前并没有一个系统性的实验对比分析揭示当前此过程面临的挑战以及可能的解决思路.文中对具有代表性的各类方法进行综合深入对比与分析.人脸画像合成方法归纳为2类:数据驱动类方法(即基于样本的方法)和模型驱动类方法.数据驱动方法由3类方法组成:基于子空间学习的方法、基于稀疏表示的方法和基于贝叶斯推断的方法.模型驱动方法直接学习照片到画像的映射关系.文中给出一些之前文献中并未发现的有意义的结论和展望.     

Spectral analysis of nonuniformly sampled data – a review

In this paper, we present a comprehensive review of methods for spectral analysis of nonuniformly sampled data. For a given finite set of nonuniformly sampled data, a reasonable way to choose the Nyquist frequency and the resampling time are discussed. The various existing methods for spectral analysis of nonuniform data are grouped and described under four broad categories: methods based on least squares; methods based on interpolation techniques; methods based on slotted resampling; methods based on continuous time models. The performance of the methods under each category is evaluated on simulated data sets. The methods are then classified according to their capabilities to handle different types of spectrum, signal models and sampling patterns. Finally the performance of the different methods is evaluated on two real life nonuniform data sets. Apart from the spectral analysis methods, methods for exact signal reconstruction from nonuniform data are also reviewed.     

肝脏及肿瘤图像分割方法综述

肝脏肿瘤是一种发病率高且恶化概率高的疾病,为了快速地诊断肝脏疾病,需要从计算机断层扫描(CT)中准确地分割出肝脏及肿瘤。为了分析肝脏及肿瘤图像分割领域的现状及发展趋势,针对肝脏及肿瘤图像的分割方法进行了研究,总结了近些年肝脏及肿瘤图像的分割方法。肝脏及肿瘤图像分割方法包括传统方法以及深度学习方法。传统方法需要较多的人工参与,不能实现完全自动化。深度学习方法从分割网络的维度可分为2D、2.5D以及3D方法,这些方法分割精度高,硬件需求高。在考虑深度学习与传统方法优缺点的同时,它们的结合也被不断探索,图割法和条件随机场等传统方法经常被用于细化深度学习方法的分割结果。     

视频检索中镜头分割方法综述

视频序列的镜头分割亦称镜头变化检测是视频检索中的关键技术之一。镜头变化是指视频序列中场景内容的变化。该文介绍了目前镜头分割的常用方法,包括灰度分割法、边缘分割法、彩色直方图分割法、MPEG视频的分割方法、块匹配镜头分割方法、统计判决镜头分割方法、基于聚类的镜头分割方法、镜头渐变的检测等,指出了研究场景内容的表征方法、特征提取方法、特征的检测尺度以及稳健可靠的实用镜头分割方法是目前主要的研究方向。     

人脸表情识别的研究进展

人脸表情识别是人机交互、机器学习、智能控制和图像处理等领域涉及的重要研究方向,目前已成为国内外研究的热点。从人脸表情识别的特征提取和特征分类两方面出发,总结了国内外近几年人脸表情识别的进展状况。在特征提取阶段,根据所处理的图像的属性,分别从静态图像和动态图像两个方面总结人脸表情的特征提取算法,前者包括整体法和局部法,后者分为模型法、光流法和几何法。在分类器的设计上,以贝叶斯网络和距离度量两条理论主线,贯穿主要的方法。最后结合国内外最新的研究成果和应用领域,展望了人脸表情识别的发展。     

Initial value problems: numerical methods and mathematics

A number of questions and results concerning Runge-Kutta and general linear methods are surveyed. These include order conditions and order bounds for Runge-Kutta methods, the A-stability of implicit Runge-Kutta methods based on Gaussian quadrature and transformation methods of implementation which lead to singly-implicit methods. The sections dealing with general linear methods include a discussion of the order conditions and an algebraic structure for carrying out order analyses as well as an introduction to a special function associated with parallel methods for stiff problems.     

无结构对等中网络资源发现方法研究的最新进展

为了提高无结构对等网络的资源查找效率,消除冗余网络流量,出现了许多查询算法。在分析这些算法特点的基础上,将它们大致分成四类：基于前向传递的方法、基于缓存的方法、基于查询和数据双重复制的方法、基于拓扑优化的方法。进一步深入分析其优缺点之后,指出任何一类查询算法都只优化了某一方面的性能,如果能将某几类方法有机集成,使它们相互补充,定能取得更好的效果。最后给出了一些重要的结论。     

A family of Numerov-type exponentially fitted methods for the numerical integration of the Schrödinger equation

A family of predictor-corrector exponential Numerov-type methods is developed for the numerical integration of the one-dimensional Schrödinger equation. The Numerov-type methods considered contain free parameters which allow it to be fitted to exponential functions. The new fourth algebraic order methods are very simple and integrate more exponential functions than both the well-known fourth order Numerov-type exponentially fitted methods and the sixth algebraic order Runge-Kutta-type methods. Numerical results also indicate that the new methods are much more accurate than the other exponentially fitted methods mentioned above.     

软件开发方法发展回顾与展望

软件是信息化社会的基础设施,而构造并运用软件的能力成为一种核心竞争力.软件开发方法凝结了系统化的软件构造过程和技术.简要回顾了50年来软件开发方法发展历程中具有重要影响的里程碑,包括基于结构化程序设计和模块化开发的基本方法、面向对象方法、软件复用与构件化方法、面向方面的方法、模型驱动的方法,以及服务化的方法.而后针对Internet的发展普及以及人机物融合应用对软件开发方法提出的挑战,介绍了网构软件的研究和探索,并展望未来人机物融合的软件方法和技术.     

Relaxed parallel two-stage multisplitting methods ∗

Two classes of relaxed parallel two-stage multisplitting methods based on extrapolated and AOR methods are studied for the solution of nonsingular linear systems, which are called outer relaxed or inner relaxed parallel two-stage multisplitting methods. Convergence of these methods is studied for H-matrix. Furthermore, computational results about these methods on a shared memory multiprocessor are presented. The results show that the methods we proposed are better than the corresponding existed parallel (two-stage) multisplitting methods.     

Methods of planning the electronic workplace

Traditional data processing methods of implementing systems have led to many human problems and have often not been successful. This paper reviews a number of alternative design methods, both centralized methods such as structured design methods, and decentralized or end user-developed systems. It concludes that, whilst the new methods are all more user-centred in concept, they may still fail because the methods necessary to deal with user issues are not widely available. The paper ends by reviewing the required methods which include task analysis, prototype evaluation, interface design and continued user support. Some examples of the required methods are provided.     

Über Matrixdarstellungen für Iterationsverfahren bei nichtlinearen Gleichungen

This note presents a matrix representation of iterative methods which is a generalization of those given by Miranker [6] and Rice [8]. It is based on an elementary theorem which show that the order of convergence of some nonlinear single-step and total-step methods is the spectral radius of a certain matrix. Thus a large class of iterative methods are easy to analyze especially such as: Hermiteinterpolatory methods, composite Hermite-interpolatory methods, several parallel methods and even special methods for systems of equations.     

时间序列分类问题的算法比较

时间序列分类是时间序列数据分析中的重要任务之一.不同于时间序列分析中常用的算法与问题,时间序列分类是要把整个时间序列当作输入,其目的是要赋予这个序列某个离散标记.它比一般分类问题困难,主要在于要分类的时间序列数据不等长,这使得一般的分类算法不能直接应用.即使是等长的时间序列,由于不同序列在相同位置的数值一般不可直接比较,一般的分类算法依然还是不适合直接应用.为了解决这些难点,通常有两种方法:第一,定义合适的距离度量(这里,最常用的距离度量是DTW距离),使得在此度量意义下相近的序列有相同的分类标签,这类方法属于领域无关的方法;第二,首先对时间序列建模(利用序列中前后数据的依赖关系建立模型),再用模型参数组成等长向量来表示每条序列,最后用一般的分类算法进行训练和分类,这类方法属于领域相关的方法.长期以来,研究者往往只倾向于使用其中一种算法,而这两类算法的比较却比较缺乏.文中深入分析了这两类方法,并且分别在不同的合成数据集和实际数据集上比较了两类方法.作者观测到了两类算法在不同因素影响下的性能表现,从而为今后发展新的算法提供了有力依据.     

Monte Carlo comparisons of selected clustering procedures

Monte Carlo methods were used to estimate the percent misclassification of 13 clustering methods for six types of parameterizations of two bivariate normal populations. The clustering methods were compared by using the probabilities of misclassification and incidence matrices. It was determined that correlations and differences in population sizes adversely influenced all clustering methods, where differences in the variance structure did not appreciably affect the results. The k-means partitioning method was the overall best method. Considering only agglomerative methods, the sum of squares, variance, furthest neighbor and rank score methods were generally superior to the other non-partitioning methods considered. The overall poorest methods were judged to be nearest neighbor and maximum likelihood. However, as the complexity of the distributions increased, the differences between all of the methods decreased.     

Discrete gradient methods and linear projection methods for preserving a conserved quantity of stochastic differential equations

Numerical methods preserving a conserved quantity for stochastic differential equations are considered. A class of discrete gradient methods based on the skew-gradient form is constructed, and the sufficient condition of convergence order 1 in the mean-square sense is given. Then a class of linear projection methods is constructed. The relationship of the two classes of methods for preserving a conserved quantity is proved, which is, the constructed linear projection methods can be considered as a subset of the constructed discrete gradient methods. Numerical experiments verify our theory and show the efficiency of proposed numerical methods.     

Vague值向Fuzzy值转化方法新探

用反例证明文献[1]提出的两种Vague值向Fuzzy值的转化方法是不满足准则1^[2]和准则2^[2]的。但是如果在这两个方法中补充参数的约束条件,则这两种方法皆是实用方法。提出两种Vague值向Fuzzy值新的转化方法,证明了它们是实用方法。     

An analysis of the traditional IS security approaches: implications for research and practice

Scholars have developed several modern information systems security (ISS) methods. Yet the traditional ISS methods – ISS checklists, ISS standards, ISS maturity criteria, risk management (RM) and formal methods (FM) – are still among the most used ISS methods. This study makes sense of these traditional ISS methods by comparing their underlying key assumptions. The main finding is that the traditional ISS methods regurgitate several features and assumptions that are required to be dealt with by traditional ISS methods developers and practitioners.     

图象分割评价技术分类和比较

本文对图象分割评价，特别是评价方法和评价准则的进展，作了一个综述，现已提出的多数分割评价方法可分为直接法和间接法，直接法研究分割算法本身，面间接法根据分割图象来评价算法的性能。直接法和间接法都需要借助一定的评价准则来进行。本文对已提出的各种准则进行了分类与分析比较，并对常用的评价准则进行了实验比较，通过分析其性能表现排出了它们的优劣次序。本研究为在实际中正确地应用不同的评价方法提出了依据并指出了若干进一步研究的方向。