一种基于几何的形计算机制

提出一种几何问题几何化的形计算机制。它综合了几何、代数、画法几何及现代计 算工具等理论、方法与技术,实现“三维思维,二维图解,一维计算”多维空间的融合。从更宏 观的几何角度构筑算法框架,是对常规数计算的补充,可用于相当宽泛的一类几何计算。     

点模型的多分辨率形状编辑

提出了一种基于几何细节映射的点模型的形状编辑方法.几何细节是曲面的一个重要属性,定义几何细节为原始曲面及其基曲面之间的向量差,该基曲面由多层次B样条所构成.通过基曲面上的局部仿射坐标,则可以得到与之对应的多分辨率几何细节表示,曲面的低频信息和高频信息易被用户所指定的频段分离.通过调节基曲面的形状,再将这些几何细节映射上去,可以对模型进行保细节的变形;如果将几何细节映射到其他物体上,将可以得到几何细节迁移的结果.为点模型开发了多种特征保持的编辑算子,实验结果表明,所提出的方法是一种有效的点模型造型算法.     

基于 Windows GDI+ 的几何形状测量

介绍了利用GD I+的G raph icsPath类和R eg ion类对几何线条的长度、几何线条所围区域的面积的测量方法,并对其中的关键部分提供了示例代码。与传统的数学微积分方法相比,不需要复杂的数学运算和高深的数学功底。     

Weighted Average Errors in Set-Membership Estimation

Average-case analysis provides knowledge about the quality of estimation algorithms in the case when the influence of outliers (exceptionally difficult elements) is to be neglected. This is in contrast with the worst-case analysis, where exceptionally difficult elements are of particular interest. In this paper we consider the average behavior of estimation algorithms based on corrupted information, with values in a subspace of the problem element space. We study two local average errors, with respect to probability measures defined by a class of weight functions. We define the optimal algorithm and derive exact error formulas, in Euclidean norms in problem element and information spaces. The formulas explicitly show the dependence of the errors on basic components of the problem, in particular on the weights. Attention is paid to the class of isotropic weight functions, examples of which are provided by truncated Gaussian weight functions. An extension of the results to non-Euclidean norms in the information space in a special case is shown. Date received: July 19, 2002. Date revised: January 9, 2003. This research was partly supported by AGH Grant No. 10.420.03.     

一种基于扩散几何的非刚体三维形状分割方法

三维形状分割是三维形状分析中的一个重要问题.为了使分割结果能适应非刚体丰富的姿态变化,提出一种基于扩散几何的三维网格分割方法.该方法采用波核特征的局部极值点作为非刚体网格模型表面的显著特征点;进而将显著特征点作为初始聚类中心,采用K-均值聚类算法来获得分割结果.实验结果表明,文中方法不仅对处于不同姿态的非刚体三维形状具有良好的分割一致性,而且对噪声、孔洞等具有较好的鲁棒性.     

基于Bayes网的软件残留错误数度量

软件开发的复杂性决定了理想的软件复杂性度量模型既应具有包容众多复杂因素的能力,又要有构造灵活的功能。迄今为止，人们提出的众多模型，由于设定了很多近乎苛刻的条件，使它们难以具有普适性。Bayes网提供了解决这一问题的有力工具。该文建立起一种基于Baycs网的软件残留错误数度量模型，并对此进行了分析。     

信道估计误差对功率分配算法的影响分析

自适应功率分配技术可以最大限度提高OFDM传输系统的信道容量和传输质量.是多用户OFDM系统中的关键技术.分析和比较了非理想信道估计情况下,信道估计误差对当前三种主要OFDM适应功率分配算法性能的影响.仿真结果表明,无论是理想信道估计还是存在误差的非理想信道估计条件下.理想频谱平衡算法和迭代频谱平衡算法的性能总是优于迭代注水算法.但是,随着信道估计误差的不断增大,迭代注水算法的性能具有较好的稳健性.对设计实际系统有重要的指导意义.     

基于曲面形状误差的多层前向神经网络快速训练

如何显著提高多层前向神经网络训练速度一直是国内外共同关注的一个问题,而解决这个问题的关键在于充分了解导致现有网络训练算法训练效率低的根本原因．文中首先提出了网络输出函数的曲面形状误差和偏移误差的概念,并将指导网络训练的平方和误差分解为这两种误差,进而分析了这两种误差的主要特性,给出了导致现有算法网络训练效率低的主要原因,最后提出了新的网络训练误差模型和具体的网络训练算法．典型实例计算结果表明,与目前常用的网络训练算法相比,该文所提出的算法可显著减少网络训练时间。     

基于软错误的动态程序可靠性分析和评估

基于软件实现的软错误容错方法不需要硬件开销,被认为是一种高效的软错误容错方法,而动态的实现这种方法能覆盖更多种类型的程序,因而能覆盖更多的软错误,分析硬件软错误对程序执行时代码和数据的逻辑影响,并建立了硬件软错误条件下程序运行可靠性评估模型.本文的工作为基于软件动态软错误容错算法的提出提供了理论基础,也为程序可靠性的评估提供了一种方法.我们依据体系结构层硬件对指令执行的影响将硬件构件进行分类,并分析了不同的硬件构件对程序代码和数据的逻辑影响.基于软错误对程序代码和数据的影响模型,建立了软错误条件下程序运行可靠性评估模型.最后,在实验中,对软错误条件下程序影响模型和程序运行可靠性评估模型进行了验证,实验结果证明了本文的分析和评估结果.     

Estimation and Modeling of Actual Numerical Errors in Volume Rendering

In this paper we study the comprehensive effects on volume rendered images due to numerical errors caused by the use of finite precision for data representation and processing. To estimate actual error behavior we conduct a thorough study using a volume renderer implemented with arbitrary floating‐point precision. Based on the experimental data we then model the impact of floating‐point pipeline precision, sampling frequency and fixed‐point input data quantization on the fidelity of rendered images. We introduce three models, an average model, which does not adapt to different data nor varying transfer functions, as well as two adaptive models that take the intricacies of a new data set and transfer function into account by adapting themselves given a few different images rendered. We also test and validate our models based on new data that was not used during our model building.     

Robust Estimation for an Inverse Problem Arising in Multiview Geometry

We propose a new approach to the problem of robust estimation for a class of inverse problems arising in multiview geometry. Inspired by recent advances in the statistical theory of recovering sparse vectors, we define our estimator as a Bayesian maximum a posteriori with multivariate Laplace prior on the vector describing the outliers. This leads to an estimator in which the fidelity to the data is measured by the L _??-norm while the regularization is done by the L ₁-norm. The proposed procedure is fairly fast since the outlier removal is done by solving one linear program (LP). An important difference compared to existing algorithms is that for our estimator it is not necessary to specify neither the number nor the proportion of the outliers; only an upper bound on the maximal measurement error for the inliers should be specified. We present theoretical results assessing the accuracy of our procedure, as well as numerical examples illustrating its efficiency on synthetic and real data.     

图像中广义高斯噪声形状参数的近似估计

针对图像中广义高斯噪声的形状参数p通常为未知的问题,提出一种用于计算p的近似矩估计算法。从原图像中提取噪声样本,采用分段函数对p的比率函数进行数值拟合,从而得到p的近似表达式。实验结果表明,当噪声样本值准确时,p的估计值能精确到小数点后2位,尤其适用于均匀噪声的情况,估计误差比传统算法小0.3;当噪声样本值不准确时,估计精度与门限K的选择有关。     

Effects of Aliasing Errors on Microlithographic Image Computations

Recent advances in computational microelectronics have made it possible to compute the images of very large masks. Images of entire masks require many gigabytes of storage. It is therefore desirable to make storage requirements as small as possible. In this paper, we investigate the effects of reducing resolution to the point where some aliasing error enters the final answer. Due to the accuracy requirements of the microelectronics industry, we conclude that reducing resolution to improve storage requirements is not feasible.     

Stable Neuro-Adaptive Control for Robots with the Upper Bound Estimation on the Neural Approximation Errors

An indirect adaptive control approach is developed in this paper for robots with unknown nonlinear dynamics using neural networks (NNs). A key property of the proposed approach is that the actual joint angle values in the control law are replaced by the desired joint angles, angle velocities and accelerators, and the bound on the NN reconstruction errors is assumed to be unknown. Main theoretical results for designing such a neuro-controller are given, and the control performance of the proposed controller is verified with simulation studies.     

基于辅助阵元的阵元位置误差和信源方位联合估计算法

鉴于阵元位置误差会严重影响MUSIC算法的测向性能,基于W-F方法的思想给出了一种基于辅助阵元的阵元位王误差和信源方位联合估计算法.该算法可看作是W-F方法的一种变形,因为它仍以交替迭代的方式给出,其目标函数建立在信号子空间性质的基础上,并且可推广应用于任意阵列流型.同时本文推导了各个参数估计的克拉美罗下界(CRLB),仿真结果验证了本文算法的有效性.     

联合定轨测量组合系统误差参数估计算法

研究航天器数据测量,针对联合定轨距离和测元上可能存在的组合系统误差特性,在讨论各种典型系统误差诊断方法与参数估计算法的基础上,为了提高系统定轨精度.提出了一种摹于奇偶方程的测量组合系统误差诊断识别方法,建立了联合定轨测量组合系统误差的参数估计算法.理论分析和仿真计算结果表明,提出的方法能够实现对联合定轨距离和测元上的多种类型的组合误差进行检测与参数估计,并取得满意结果.     

Confounding in the Estimation of Mediation Effects

A mediation effect explains the relationship of a risk factor and an outcome through a mediator variable which is a step in their pathway. Under the assumption of no cycling in the causal relationship, we consider various situations in which a fourth variable may interfere the estimation of a mediation effect as a confounding factor. Our asymptotic results, which are supported by a Monte Carlo study, show that adjusting for confounding factors under certain conditions might lead to biased estimates. A general guideline is provided for when it is appropriate to adjust for confounding factors in estimating a mediation effect. We apply the guideline to the estimation of the mediation effect of Alzheimer's disease pathology in the relationship between the Apolipoprotein E ε4 allele and cognitive function among 125 deceased participants from the Religious Orders Study, a longitudinal, clinical-pathologic study of aging and Alzheimer's disease.     

Estimation of Shape Parameter of GGD Function by Negentropy Matching

In this paper we present a novel method for the estimation of the shape parameter of the Generalized Gaussian Distribution (GGD) function for the leptokurtic and Gaussian signals by matching negentropy of GGD function and that of data approximated by some non-polynomial functions. The negentropy of GGD function is monotonic function of its shape parameter for values corresponding to super-Gaussian and Gaussian distribution family. The simulation results have been compared with those obtained by existing methods such as Mallat’s method and Kurtosis matching method. It has been found that the proposed method is effective and useful in the cases where we have a few observation samples and distribution is highly spiky.     

形状参数对MEMS霍尔器件性能影响研究

利用有限元分析软件ANSYS对长方形和圆形两种霍尔器件的工作状态进行模拟,分析霍尔片(霍尔器件工件区域)结构尺寸与霍尔器件灵敏度的关系,研究形状对器件灵敏度的影响.结果表明:圆形霍尔片灵敏度比长方形霍尔片的高,当圆形霍尔片的半径与厚度比值为15时,灵敏度最高.     

Robust Estimation of Albedo for Illumination-Invariant Matching and Shape Recovery

We present a nonstationary stochastic filtering framework for the task of albedo estimation from a single image. There are several approaches in the literature for albedo estimation, but few include the errors in estimates of surface normals and light source direction to improve the albedo estimate. The proposed approach effectively utilizes the error statistics of surface normals and illumination direction for robust estimation of albedo, for images illuminated by single and multiple light sources. The albedo estimate obtained is subsequently used to generate albedo-free normalized images for recovering the shape of an object. Traditional Shape-from-Shading (SFS) approaches often assume constant/piecewise constant albedo and known light source direction to recover the underlying shape. Using the estimated albedo, the general problem of estimating the shape of an object with varying albedo map and unknown illumination source is reduced to one that can be handled by traditional SFS approaches. Experimental results are provided to show the effectiveness of the approach and its application to illumination-invariant matching and shape recovery. The estimated albedo maps are compared with the ground truth. The maps are used as illumination-invariant signatures for the task of face recognition across illumination variations. The recognition results obtained compare well with the current state-of-the-art approaches. Impressive shape recovery results are obtained using images downloaded from the Web with little control over imaging conditions. The recovered shapes are also used to synthesize novel views under novel illumination conditions.