基于协作波束形成的中继阻塞混合无线物理层安全传输

针对双向无线协作通信系统的安全传输(信息论安全)问题,提出一种基于多节点协作波束形成的中继与阻塞混合机制来提高物理层信息传输的安全性.其基本思想是:在协作传输阶段,系统中的一部分协作节点进行分布式波束形成来帮助发送方发送信息给合法用户,同时另一部分协作节点发送干扰信号阻塞窃听者的侦听,从而显著改善系统在协作广播阶段的安全性能.基于这一机制,针对窃听者的瞬时信道状态信息已知与否,本文提出两种不同的协作波束形成方法和优化方案,这两种方案在数学上均归结为解决一个或一系列的二阶凸锥规划问题,从而可以通过内点法有效地求解.仿真结果和对比实验验证了在中继节点数目较多时本文提出的混合安全机制和波束形成方法相对于单纯的协作中继机制或单纯的协作阻塞机制而言显著地提高了系统的物理层安全性能.     

用于多天线通信系统的自适应波束形成与空时块码相结合方案

针对多天线通信系统,提出了一种将自适应波束形成(ABF)与空时块码(STBC)相结合的下行链路发射方案.首先基于STBC所产生的等效加权加性Gauss白噪声(AWGN)信道模型,求得接收平均信噪比(SNR)最大化条件下的发射端自适应波束形成权矢量.接着以常用的3大类调制方式下的误符号率(SER)上界为准则,设计出各个波束间的最优功率分配算法.该发射方案实际上是对应于信道自相关矩阵的特征波束形成,同时结合空时编码以获得分集增益,从而提高无线通信下行链路的性能.此外,基于矩生成函数(MGF)和Gauss-Chebyshev积分,还提出了一种简单而精确的数值计算方法,用来分析采用新方案的通信系统在常用调制方式下的性能.最后计算机仿真结果验证了新方案的性能优于常用的空时块码和现有相关文献上介绍的方法.     

月球轨道器交会对接同波束VLBI测量差分相时延实时解算

同波束VLBI技术是解决月球轨道交会对接地面高精度引导的重要手段．传统的多频点同波束VLBI实时解算算法成功解算差分相位整周模糊度的概率较低,而事后统计修正求解整周模糊度的算法存在较大的时间滞后,从而直接影响月球轨道交会对接两个航天器地面定轨、定位的精度以及实时性．在此背景下,本文研究了应用于月球交会对接条件下的同波束VLBI差分相时延实时解算算法．首先给出了多频点同波束VLBI解算差分相时延及整周模糊度的原理,根据差分相关相位整周模糊和差分相时延实时及事后解算结果,对整周模糊度产生的原因进行分析通过求解精确差分群时延值、采用匹配搜索算法以及差分相位连接条件对传统实时解算算法进行改进,提出一种新的差分相时延实时解算算法．利用SELENE同波束VLBI观测数据进行实时解算．结果表明该算法成功解算模糊度的准确度达到95．49％,相对于传统解算算法准确度提高了5．45％．     

基于SIAR体制的单基地MIMO雷达方向综合及测角性能分析

针对同时辐射多载频的正交信号、收发天线稀布且不共用的单基地MIMO雷达,以及在低仰角目标回波存在多径现象的情况下,提出一种基于SIAR体制的单基地MIMO雷达的方向综合方法,即综合利用MIMO的发射天线和接收天线孔径,在方位和俯仰两维数字波束形成（DBF）;并结合多载频工作的MIMO雷达,研究了基于多径相干信号分离的面阵广义MUSIC算法．该方法将发射天线、接收天线的相位延迟同时补偿,在接收端对发射波束进行两维方向综合,提高了雷达的角分辨力和测角精度;并通过降维处理减少了运算量．最后给出了多径情况下,单基地MIMO雷达方位、俯仰二维角度估计的克拉美·罗界（CRB）．计算机仿真证实了该方法的有效性．     

基于有限反馈的协作多小区分布式预编码

多小区协作需要基站间交换大量的信息.为了降低无线回传开销和反馈开销,采用基于信漏噪比最大化的分布式预编码方法,该方法仅需共享干扰信道的信道状态信息,不需要共享数据,与特征值波束成形和小区间干扰清零两种极端的方法相比取得了性能提高.其次,为了更加有效利用反馈资源,推导了速率损耗公式,利用穷尽搜索得到使其最小化的最优解,得出比特自适应分配规律.仿真表明,根据期望信号和干扰信号强度自适应的分配反馈比特能进一步提高系统速率.     

相控阵多址系统中通道间群时延不一致性分析

首先从数学公式分析了多用户相控阵通信系统的通道时延将会引起调制数据过零点出现偏移;再针对多通道时延不一致的情况,通过理论和仿真分析发现,如果空分处理前不进行通道间时延均衡而直接进行数字波束形成处理,会使得输出信号失真,系统误码性能恶化.     

认知无线电系统中的多中继分布式波束成形方法

本文考虑认知无线电系统中一对认知源目的节点在一组认知中继节点协助下与一对授权发射机和接收机共存的场景,研究了多个单天线认知中继节点在授权接收机处平均干扰功率门限约束及自身独立的平均发射功率约束下,最大化认知目的节点处信干噪比(SINR)的分布式波束成形,从而开发"空谱空洞"的问题.提出了两种波束成形方案:1)最大化SINR的最优策略;2)基于迫零准则的次优策略.最优策略将分布式的波束成形系数求解问题通过半定松弛转化为准凸的优化问题,从而利用二分法及内点法求解;并证明了求得的最优半定松弛解即为原优化问题的最优解.次优策略直接迫零对授权接收机造成干扰,并将来自授权发射机的干扰信号抑制为零.该方法对应的优化问题没有迭代运算,且约束函数简单,算法复杂度低.最后通过数值仿真分析了中继数、认知节点最大的发射功率和授权接收机的干扰功率门限等因素对两类算法平均传输速率的影响,并且通过对比实验验证了考虑授权发射机干扰信号影响带来的性能增益.     

基于非线性自适应神经网络的刨煤机刨头位置控制系统

由于多种因素影响刨煤机刨头位置的控制，本文提出了一种基于非线性自适应神经网络的刨煤机刨头位置控制系统，该系统采用了多传感器数据融合的方法，并将其应用在前馈反馈自适应神经网络中，其结果表明，与常规PID系统相比该系统能够消除静差从而更好地跟踪参考曲线。     

流数据驱动的多层非线性动力学网络重构

现实世界中许多复杂的非线性动力学系统需要用多层网络来描述.如何从观测到的流数据中揭示多层非线性动力学网络结构的重构问题是对动力学系统研究的核心问题之一.虽然学者们提出了许多从静态数据中重构多层动力学网络结构的方法,但是它们很难从流数据中重构多层网络结构.由于该问题的困难性,截止目前,还没有适用于流数据的多层非线性动力学网络重构模型及其优化算法.针对此,本文提出流数据驱动的多层动力学网络重构框架,称为OMNR(online multilayer network reconstruction). OMNR首先建立了流数据驱动的在线多层非线性动力学网络重构模型,然后提出一种基于FTRL(follow-the-regularized-leader)的在线学习方法来优化该模型. OMNR每次只考虑一个事例来更新网络结构,非常适合处理流数据.而且, OMNR空间复杂度非常低,适合大数据任务.最后,在多层网络的Lorenz和R?ssler动力学系统上验证了OMNR可以有效地解决流数据驱动的多层动力学网络重构问题,填补了流数据驱动的多层非线性动力学网络重构技术的空白.     

混凝土坝裂缝转异诊断的云模型法

针对现有混凝土坝裂缝转异诊断方法多是基于裂缝开度单个测点进行分析这一不足,提出利用多个测点综合信息量诊断裂缝性态的思路.根据这一思路,首先研究了将裂缝开度变化转化为裂缝信息量的方法,其次利用投影寻踪法研究了裂缝开度各测点权重的确定方式,然后将裂缝开度多个单测点的信息量归纳为综合信息量,最后根据云模型理论,建立了裂缝转异诊断的两种判据:基于裂缝信息量总体数据序列的判据,以及考虑裂缝信息量历史数据和当前数据差异性的判据,建立了裂缝转异诊断的云模型法.实例分析表明,裂缝转异诊断的云模型法能够较客观地分析历史数据和当前数据贡献以及对结果的影响,该方法具有可行性.     

手舟骨的有限元建模及其损伤分析

目的 基于医学DICOM格式的图像,不经过二次转换并快速且准确的建立舟骨有限元模型,从而得到可以用于舟骨应力分析的有限元模型,并通过模拟手舟骨损伤来分析不同的受力特点. 方法 选择健康成年男性志愿者,进行高精度螺旋CT扫描,将得到的DICOM 3.0医学图像数据,导八MIMICS医学影像软件并生成实体模型,然后应用通用有限元分析软件ANSYS 11生成有限元模型.约束边界条件,模拟舟骨轴向压力进行加载,得出舟骨有限元模型上的应力分布与应变结果,并模拟舟骨不同损伤的力学改变. 结果 建立的舟骨三维有限元模型共有节点73588个,单元397344个.所建模型结构完整,空间结构准确,单位划分精细,轴向压力作用下加栽模拟形象、逼真,客观反映舟骨三维解剖形态结构和生物力学特点. 结论 应用高精度螺旋CT成像的DICOM 3.0数据,并与MIMICS和ANSYS相结合的方法快速建立舟骨的三维有限元模型是切实有效和可行的;有限元方法可较好的分析手舟骨及其损伤的生物力学特点.     

多源异构感知数据融合方法及其在目标定位跟踪中的应用

物联网的全面感知产生了海量的感知数据,并且感知数据呈现为显著的多源异构性.因此,如何实现海量多源异构感知数据的智能处理是一个具有挑战性的课题.数据融合是处理多模态数据并挖掘提取有价值信息的有效手段,但针对多源异构数据,特别是非结构化的视频多媒体信息,如何实现高效的融合计算还面临许多问题需要解决.本文针对物联网多源异构感知信息的处理问题,提出多层次的多源异构数据融合方法,并以基于无线信号、视频和深度感知数据的目标定位跟踪应用为切入点,重点研究多源异构数据的处理、特征表示和数据融合方法.根据不同类型数据的特性采用不同的数据融合方法,通过挖掘无线信号、视频和深度等多源异构数据内在的关联性,实现多源异构数据有价值信息的有效利用.实际复杂场景的实验表明,本文提出的基于多源异构数据融合的目标跟踪和定位方法,能够解决传统依赖单源同质数据的目标跟踪方法所面临的光照变化和遮挡交错等难点问题,并且可以获得较为准确的运动目标三维位置,具有良好的跟踪定位效果.     

基于DSP＆CPLD的便携式振动信号处理系统

为了更准确方便地诊断设备运行特性,结合FFT和小波分析原理设计了一种基于DSP＆CPLD的便携式振动信号处理系统。系统的硬件电路由信号调理电路、数据采集处理模块和外围电路等组成,其软件部分由主程序模块、数据采集处理程序和LCD显示程序等组成,能够实时采集振动信号,显示并存储静态特性、振动波形和频谱等数据。     

On the origins and foundations of Laplacian determinism

In this paper I examine the foundations of Laplace’s famous statement of determinism in 1814, and argue that rather than derived from his mechanics, this statement is based on general philosophical principles, namely the principle of sufficient reason and the law of continuity. It is usually supposed that Laplace’s statement is based on the fact that each system in classical mechanics has an equation of motion which has a unique solution. But Laplace never proved this result, and in fact he could not have proven it, since it depends on a theorem about uniqueness of solutions to differential equations that was only developed later on. I show that the idea that is at the basis of Laplace’s determinism was in fact widespread in enlightenment France, and is ultimately based on a re-interpretation of Leibnizian metaphysics, specifically the principle of sufficient reason and the law of continuity. Since the law of continuity also lies at the basis of the application of differential calculus in physics, one can say that Laplace’s determinism and the idea that systems in physics can be described by differential equations with unique solutions have a common foundation.     

一种有线无线混合网络下减少TCP重复应答的跨层机制

针对有线无线混合网络中TCP ACK与MAC ACK重复应答问题,提出一种跨层设计机制。通过AP代理回复移动接收端的TCP ACK,避免了移动接收端同时发送MAC ACK和TCP ACK（移动接收端只发送MAC ACK）。该机制实现简单,只需少量修改IEEE802．11帧格式,在帧控制域中添加必要的TCP ACK类型指示和传递接收端建议窗口大小,就能有效地解决MAC到TCP包收发错误和发送端不能获取接收端接收TCP数据报文能力的问题;并且很容易在现有设备上进行升级。仿真结果表明,该机稍比传统TCP重复应答机制提高约30％的吞吐量。     

Theearly andlate processing of lysosomal enzymes: Proteolysis and compartmentation

Lysosomal enzymes are subjected to a number of modifications including carbohydrate restructuring and proteolytic maturation. Some of these reactions support lysosomal targeting, others are necessary for activation or keeping the enzyme inactive before being segregated, while still others may be adventitious. The non-segregated fraction of the enzyme is secreted and can be isolated from the medium. It is considered that the secreted lysosomal enzymes fulfill certain physiological and pathophysiological roles. By comparing the secreted and the intracellular enzymes it is possible to distinguish between the reactions that occur before and after the segregation. In this review the reactions that may influence the segregation are referred to as the early processing and those characteristic for the enzymes isolated from lysosomal compartments as the late processing. The early processing is characterized mainly by modifications of carbohydrate side chains. In the late processing, proteolytic fragmentation represents the most conspicuous changes. The review focuses on the compartmentation of the reactions and the proteolytic fragmentation of lysosomal enzyme precursors. While a plethora of proteolytic reactions are involved, our knowledge of the proteinases responsible for the particular maturation reactions remains very limited. The review points also to work with cells from patients affected with lysosomal storage disorders, which contributed to our understanding of the lysosomal apparatus.     

基于模糊C-聚类分析的回采工艺选择及MATLAB实现

煤矿生产中,各个回采工作面的地质条件是影响回采工艺选择的决定性因素,工作面回采工艺选择的合理与否,直接关系到煤炭开采的效率.由于地质因素的不确定性和模糊性,导致了在回采工艺方式选择问题上的复杂性.快速发展的模糊数学为分析这类问题提供了一个很好的解决办法.这里采用模糊数学中C-均值聚类对已采工作面进行分类,并利用分类结果对未采工作面选择何种回采工艺做出预测,这种复杂的计算过程借助了MATLAB逻辑工具箱中的C-均值聚类函数(FCM)来完成,使大量数据的分析得以实现,大大提高了数据处理的效率.     

基于共形几何代数的3D医学图像配准

随着医学图像处理技术的发展,3D／3D配准益受重视,尤其是在外科手术导航等医学应用中．学者们提出了各种3D／3D配准方法,但大多方法是采用传统代数方法进行配准,配准精度和效率都存在问题．本文利用非经典数学——共形几何代数重建了3D医学图像的位置关系约柬问题,分析了医学图像的共形几何变换,构造了新的3D医学图像配准相似测度,基于此提出了新的3D医学图像配准算法,用于CT和MR图像的3D配准．新算法中,以骨骼轮廓作为配准的基础点集,在骨骼轮廓的基础上采用共形几何代数构造共形几何体,接着采用新的3D医学图像配准相似测度进行三维数据的直接配准．实验表明新算法实现了三维数据的直接对齐,能较好地定位组织器官的三维位置．可以直观地体现配准结果．     

The early and late processing of lysosomal enzymes: proteolysis and compartmentation.

Lysosomal enzymes are subjected to a number of modifications including carbohydrate restructuring and proteolytic maturation. Some of these reactions support lysosomal targeting, others are necessary for activation or keeping the enzyme inactive before being segregated, while still others may be adventitious. The non-segregated fraction of the enzyme is secreted and can be isolated from the medium. It is considered that the secreted lysosomal enzymes fulfill certain physiological and pathophysiological roles. By comparing the secreted and the intracellular enzymes it is possible to distinguish between the reactions that occur before and after the segregation. In this review the reactions that may influence the segregation are referred to as the early processing and those characteristic for the enzymes isolated from lysosomal compartments as the late processing. The early processing is characterized mainly by modifications of carbohydrate side chains. In the late processing, proteolytic fragmentation represents the most conspicuous changes. The review focuses on the compartmentation of the reactions and the proteolytic fragmentation of lysosomal enzyme precursors. While a plethora of proteolytic reactions are involved, our knowledge of the proteinases responsible for the particular maturation reactions remains very limited. The review points also to work with cells from patients affected with lysosomal storage disorders, which contributed to our understanding of the lysosomal apparatus.     

Neural model identification,variable selection and model adequacy

In recent years an impressive array of publications has appeared claiming considerable successes of neural networks in modelling financial data but sceptical practitioners and statisticians are still raising the question of whether neural networks really are ‘a major breakthrough or just a passing fad’. A major reason for this is the lack of procedures for performing tests for misspecified models, and tests of statistical significance for the various parameters that have been estimated, which makes it difficult to assess the model's significance and the possibility that any short‐term successes that are reported might be due to ‘data mining’. In this paper we describe a methodology for neural model identification which facilitates hypothesis testing at two levels: model adequacy and variable significance. The methodology includes a model selection procedure to produce consistent estimators, a variable selection procedure based on statistical significance and a model adequacy procedure based on residuals analysis. We propose a novel, computationally efficient scheme for estimating sampling variability of arbitrarily complex statistics for neural models and apply it to variable selection. The approach is based on sampling from the asymptotic distribution of the neural model's parameters (‘parametric sampling’). Controlled simulations are used for the analysis and evaluation of our model identification methodology. A case study in tactical asset allocation is used to demonstrate how the methodology can be applied to real‐life problems in a way analogous to stepwise forward regression analysis. Neural models are contrasted to multiple linear regression. The results indicate the presence of non‐linear relationships in modelling the equity premium. Copyright © 1999 John Wiley & Sons, Ltd.