利用信息融合方法的三维特征提取

本文提出了一种基于信息融合的物体三维特征的提取方法，该方法利用两幅互相配准的三维测距图像和灰度图像，来提取多面体的三维特征。首先，通过分析灰度图像中的灰度变化及测距图像中的测距值变化，分别求取各自图像中物体的特征点及特征边；然后，利用两配准图像之间的对应关系，求得所有特征点、面与多边形在三维测距图像中的三维表示；接着，通过分析三维测距图像中所测得的各候选平面上特定点与边处的曲率及法向，验证候选平面     

Outlier-resistant methods for estimation and model fitting

Least squares is perhaps the most widely used technique for model fitting. In this article, we illustrate the poor performance of least squares when there are spurious values, or outliers, in a sequence of measurements. A brief overview of three well-known classes of robust alternatives to the least-squares mean is presented. For robust regression, a recent proposal called least median squares (LMS) is decribed. LMS regression is compared to least-squares regression in an example involving the estimation of optical fiber geometry. References are provided for software that is available for robust estimation techniques surveyed in this article.     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

线性调频相干激光雷达的信号处理

分析了相干激光雷达线性调频脉冲的产生及其信号处理过程，讨论了该雷达信号体制的处理方法和结果。计算了采用匹配滤波和加权处理结果，对于1MHz／μs的调制速率信号的结果表明，激光相干雷达的测速和测距精度分别可达0.04m／s和0．57m.     

用金字塔图法匹配边界图象的三眼立体视觉方法

本文在分析了双眼立体视觉面临的本质困难之后，提出了用金字塔图法匹配特征基元的三眼立体视觉方法，这种方法由于建筑在透视投影几何原理的稳固基础上，无须任何先验限制，也不以图象相似性为基础，故可较好地解决精度与匹配难度的矛盾，且运用金字塔图法进行匹配传播使在保证精度的基础上，匹配速度大大提高，对计算机人工图象的匹配结果表明，误匹配率几乎为零，且有较高的匹配速度和精度。     

COLLISION DETECTION AMONG MOVING OBJECTSIN MACHINING PROCESS SIMULATION

ＣＯＬＬＩＳＩＯＮＤＥＴＥＣＴＩＯＮＡＭＯＮＧＭＯＶＩＮＧＯＢＪＥＣＴＳＩＮＭＡＣＨＩＮＩＮＧＰＲＯＣＥＳＳＳＩＭＵＬＡＴＩＯＮＹａｎｇＨｅｍｉｎｇ；ＬｕＡｎｓｈｅｎｇ；ＺｈｏｕＪｉＣＯＬＬＩＳＩＯＮＤＥＴＥＣＴＩＯＮＡＭＯＮＧＭＯＶＩＮＧＯＢＪＥＣ...     

A STEP-BASED CAD/CAPP INTEGRATION

ＡＳＴＥＰ－ＢＡＳＥＤＣＡＤＩＣＡＰＰＩＮＴＥＧＲＡＴＩＯＮＺｈｅｎｇＬｉａｎｙｕ；ＤｕＰｅｉＡＳＴＥＰ－ＢＡＳＥＤＣＡＤＩＣＡＰＰＩＮＴＥＧＲＡＴＩＯＮ￥ＺｈｅｎｇＬｉａｎｙｕ；ＤｕＰｅｉＡｂｓｔｒａｃｔＴｈｅｉｎｆｏｒｍａｔｉｏｎｉｎｔｅｇｒａｔ...     

双相活齿泵的工作原理

在活齿传动理论及齿轮泵工作原理相结合的基础上，介绍了双相活齿泵的结构及其工作原理，研究结果表明，双相活齿泵具有流量大、流量均匀性好、噪声低以及可变量等优点。     

柳沟庄—窟窿山油藏储集层裂缝类型及特征

根据岩心描述、薄片观察、X－CT扫描以及钻井、测井等资料，研究了酒西盆地青西坳陷柳沟庄－窟窿山油藏裂缝性储集层的类型及特征，分析了控制裂缝发育的地质因素及裂缝对油气的控制作用，认为储集层裂缝有3种基本类型，即构造裂缝、构造熔蚀缝和饼状破裂，主要受构造应力场及构造位置等因素的控制。根据裂缝形态、充填特征及其相互关系，裂缝的形成主要有3个期次，其中喜马拉雅运动晚期形成的第三期理解缝对油气运移和聚集最有效。研究结果表明，裂缝是柳沟庄－窟窿山油藏主要的储集空间和控制油气富集的因素。