Orthogonality of inductosyn angle-measuring system error and error-separating technology

0　INTRODUCTIONRoundinductosynhasadvantagesofhighprecision ,goodreliabilityandassemblingconveniently[1,2 ] .Itsangle measuringerrorsincludemainlythefirst orderlong period(36 0°)harmonicerror ,thesecond orderlong periodhar monicerror,thefirst ordershort periodharmonicerrorandthesecond ordershort periodharmonicerror .Aimingata36 0 poleroundinductosyn[4 ] ,Ref.[5 ]putsforwardamethodofhardwarecompensationforthefirst ordershort periodharmonicerrorandthesecond ordershort periodharmonicerror.T…     

一体化跟踪型测角系统的误差分析

为满足系统对位置检测的要求，有利于电机系统的小型化设计，提出了采用感应同步器与单片集成轴角变换器(AD2S80A)构成的跟踪型测角系统同时作为磁极位置检测环节和角度测量系统的一体化方案．分析了感应同步器及跟踪型测角系统误差，推导了由非有效电势产生的零位奇偶跳动导致的一次正弦变化测角误差等误差模型。实验结果证明了分析方法的正确性．     

贝叶斯融合在SAR图像分类中的应用

本文研究将数据融合理论用于SAR图像分类.通过贝叶斯理论进行多通道SAR图像测量级数据融合,充分利用像素的从属信息并获得单通道分类无法获取的分类结果,有效保留各通道有用信息并抑制图像中的斑点噪声;针对贝叶斯融合涉及到的先验概率的问题采用两种方式进行先验概率估计,对估计引起的马赛克现象提出了三种解决方法;并提出三种先验概率融合方法,比较得出相对最优的SAR图像多通道分类方案.     

IP网端到端性能测量技术研究的进展

本文介绍了Internet端到端测量技术的最新进展,包括性能拓扑推测、时延测量、丢包率测量.最后讨论了未来Internet端到端测量的研究趋势和应用前景.     

分层空时码检测算法的研究

分层空时码技术是提高无线信道传输速率的一种十分有效的方法.迫零检测算法和最小均方误差检测算法是分层空时码体制中经常使用的两种检测算法,它们都使用了通常的线性合并置零技术,因此要求接收天线数不小于发射天线数,即要求在接收机上安装较多的天线,从而限制了分层空时码在移动环境下的应用.本文引入分层空时码的最大似然检测算法,突破了前两种算法对接收天线数的限制,并分别针对单路径和多径衰落信道环境,对分层空时码的三种检测算法的性能进行了仿真比较和分析,从而提出了它们各自适合的应用环境.     

Move limits definition in structural optimization with sequential linear programming. Part II: Numerical examples

A variety of numerical methods have been proposed in literature in purpose to deal with the complexity and non-linearity of structural optimization problems. In practical design, sequential linear programming (SLP) is very popular because of its inherent simplicity and because linear solvers (e.g. Simplex) are easily available. However, SLP performance is sensitive to the definition of proper move limits for the design variables which task itself often involves considerable heuristics. This research presents a new SLP algorithm (LESLP) that implements an advanced technique for defining the move limits. The linearization error sequential linear programming (LESLP) algorithm is formulated so to overcome the traditional limitations of the SLP method. In a companion paper [Comput. Struct. 81 (2003) 197] the basics of the LESLP formulation along with a guide to programming are provided.The new algorithm is successfully tested in weight minimisation problems of truss structures with up to hundreds of design variables and thousands of constraints: sizing and configuration problems are considered. Optimization problems of non-truss structures are also presented. The numerical efficiency, advantages and drawbacks of LESLP are discussed and compared to those of other SLP algorithms recently published or implemented in commercial software packages.     

一种数字图像盲增强的新算法

给出一种数字图像盲增强的新算法. 其中源数字图像及其灰度级未知, 已知的仅仅是被噪声污染了的图像. 该算法首先估计密度函数, 然后估计图像的灰度级, 最后去噪声重建图像, 达到图像增强的目的. 仿真例子说明了该算法的有效性.     

宏移动协议和微移动协议中包丢失率的比较

移动IP是支持IP移动性的协议,但是当其用于移动节点驻留在远离归属网络的外地网络时,将会产生严重的注册延迟,从而引起严重的包丢失和通信吞吐量的下降,为了改变这些不足,人们把移动节点的移动方式分为宏移动和微移动,并且提出了很多应用于微移动的移动性管理方案。文章深入研究了宏移动协议(RFC2002)和微移动协议的包丢失率,给出了计算公式,并且对计算结果进行了详细的分析。     

Practical implementation of possibilistic probability mass functions

 Probability assessments of events are often linguistic in nature. We model them by means of possibilistic probabilities (a version of Zadeh's fuzzy probabilities with a behavioural interpretation) with a suitable shape for practical implementation (on a computer). Employing the tools of interval analysis and the theory of imprecise probabilities we argue that the verification of coherence for these possibilistic probabilities, the corrections of non-coherent to coherent possibilistic probabilities and their extension to other events and gambles can be performed by finite and exact algorithms. The model can furthermore be transformed into an imprecise first-order model, useful for decision making and statistical inference.     

Analysis of a Classifier with Random Thresholds

A neural classifier with random thresholds is considered. Probabilistic analysis of functional characteristics depending on the classifier parameters is performed, and recommendations for their selection are made. The classifier structure optimization is proposed for input data distribution.