Microlocal Analysis of the Bochner-Martinelli Integral

In order to characterise the C ^* -algebra generated by the singular Bochner-Martinelli integral over a smooth closed hypersurfaces in , we compute its principal symbol. We show then that the Szeg? projection belongs to the strong closure of the algebra generated by the singular Bochner-Martinelli integral.     

周期数据时段划分的双截断高斯混合模型及其EM算法

有限混合模型是多模态数据拟合和聚类的有力工具,本文针对具有多模态的周期数据提出了双截断高斯混合糢型,并推导出相应的EM算法,再通过BIC准則确定混合成分个数,该方法的优点是可以将相邻周期上距离较近的数据聚为一类.模拟研究显示,在具体参数设置下,EM算法和BIC准则是相合的。最后,该方法应用于车流量数据的时段划分,将一天划分为具有显著特征的6个时段,有助于交通部门采取相应策略,为优化交通灯信号配时提供参考依据.     

Microlocal Analysis of Synthetic Aperture Radar Imaging

We consider Synthetic Aperture Radar (SAR) in which backscattered waves are measured from locations along a single flight path of an aircraft. Emphasis is on the case where it is not possible to form a beam with the radar. The article uses a scalar linearized mathematical model of scattering, based on the wave equation. This leads to a forward (scattering) operator, which maps singularities in the coefficient of the wave equation (viewed as a singular perturbation about a constant coefficient) to singularities in the scattered wave field. The goal of SAR is to recover a picture of the singular support of the coefficient, i.e., an a image of the underlying terrain. Traditionally, images are produced by backprojecting the data. This is done by applying the adjoint of the scattering operator to the data. This backprojected image is equivalent to that obtained by applying to the perturbed coefficient the composition of the scattering operator followed by its adjoint. We analyze this composite operator, and show that it is a paired Lagrangian operator. The properties of such operators explain the origin of certain artifacts in the backprojected image.     

Empirical Likelihood Ratio With Arbitrarily Censored/Truncated Data by EM Algorithm

The empirical likelihood is a general nonparametric inference procedure with many desirable properties. Recently, theoretical results for empirical likelihood with certain censored/truncated data have been developed. However, the computation of empirical likelihood ratios with censored/truncated data is often nontrivial. This article proposes a modified self-consistent/EM algorithm to compute a class of empirical likelihood ratios for arbitrarily censored/truncated data with a mean type constraint. Simulations show that the chi-square approximations of the log-empirical likelihood ratio perform well. Examples and simulations are given in the following cases: (1) right-censored data with a mean parameter; and (2) left-truncated and right-censored data with a mean type parameter.     

Prediction and Inference for Truncated Spatial Data

Abstract

Spatial data in mining, hydrology, and pollution monitoring commonly have a substantial proportion of zeros. One way to model such data is to suppose that some pointwise transformation of the observations follows the law of a truncated Gaussian random field. This article considers Monte Carlo methods for prediction and inference problems based on this model. In particular, a method for computing the conditional distribution of the random field at an unobserved location, given the data, is described. These results are compared to those obtained by simple kriging and indicator cokriging. Simple kriging is shown to give highly misleading results about conditional distributions; indicator cokriging does quite a bit better but still can give answers that are substantially different from the conditional distributions. A slight modification of this basic technique is developed for calculating the likelihood function for such models, which provides a method for computing maximum likelihood estimates of unknown parameters and Bayesian predictive distributions for values of the process at unobserved locations.     

Lorenz Curve for Truncated and Censored Data

In this paper, we consider a nonparametric estimator of the Lorenz curve and Gini index when the data are subjected to random left truncation and right censorship. Strong Gaussian approximations for the associated Lorenz process are established under appropriate assumptions. A law of the iterated logarithm for the Lorenz curve is also derived. Lastly, we obtain a central limit theorem for the corresponding Gini index.     

The Primal-Dual Second-Order Cone Approximations Algorithm for Symmetric Cone Programming

Given any open convex cone K, a logarithmically homogeneous, self-concordant barrier for K, and any positive real number r < 1, we associate, with each direction , a second-order cone containing K. We show that K is the interior of the intersection of the second-order cones , as x ranges over all directions in K. Using these second-order cones as approximations to cones of symmetric, positive definite matrices, we develop a new polynomial-time primal-dual interior-point algorithm for semidefinite programming. The algorithm is extended to symmetric cone programming via the relation between symmetric cones and Euclidean Jordan algebras.     

A Special Algorithm for an Additive Model in Data Envelopment Analysis

A special algorithm is presented for the additive model in data envelopment analysis (DEA). The special algorithm first classifies a data set into several subsets. Then the subset is solved by a different algorithmic framework. In simulation studies, the algorithm outperformed available DEA codes. The proposed algorithm can efficiently deal with a large data set.     

非线性偏微分方程的微局部分析

这是一篇介绍当前方程界十分重要的课题——非线性微局部分析——的综述文章。作为这一研究领域的开拓者,我们在不太长的篇幅里,从相当的理论高度简洁地介绍该领域近十年来一些最引人注目的工作。本文首先阐述了一般微局部分析的基本思想,然后介绍近十年来对非线性偏微分方程起重要推动作用的仿微分计算(如仿乘积,仿微分算子,仿复合等),以及有着更深刻内容的高次微局部的思想。同时,也大量介绍这些思想在非线性偏微分方程弱奇性分析中的应用,如奇性的传播,反射与绕射,余法型奇性的相互作用,非线性亚椭圆性,以及三个奇性波的相互作用等,这些均是当前方程界的热门课题。     

Microlocal Analysis of the Geometric Separation Problem

Image data are often composed of two or more geometrically distinct constituents; in galaxy catalogs, for instance, one sees a mixture of pointlike structures (galaxy superclusters) and curvelike structures (filaments). It would be ideal to process a single image and extract two geometrically “pure” images, each one containing features from only one of the two geometric constituents. This seems to be a seriously underdetermined problem but recent empirical work achieved highly persuasive separations. We present a theoretical analysis showing that accurate geometric separation of point and curve singularities can be achieved by minimizing the ?₁ norm of the representing coefficients in two geometrically complementary frames: wavelets and curvelets. Driving our analysis is a specific property of the ideal (but unachievable) representation where each content type is expanded in the frame best adapted to it. This ideal representation has the property that important coefficients are clustered geometrically in phase space, and that at fine scales, there is very little coherence between a cluster of elements in one frame expansion and individual elements in the complementary frame. We formally introduce notions of cluster coherence and clustered sparsity and use this machinery to show that the underdetermined systems of linear equations can be stably solved by ?₁ minimization; microlocal phase space helps organize the calculations that cluster coherence requires. © 2012 Wiley Periodicals, Inc.     

随机截断下PL估计的强表示式

本文在随机左截断情形下,研究了分布函数不连续时,分布函数的乘积限估计（PL估计）Fn(x）的一致强表示式,得到与分布函数连续情形下相同的结果。     

Analysing Policy Effectiveness Using Cone Restricted Data Envelopment Analysis

Reducing weight flexibility has been suggested as a method for ensuring that the solution to data envelopment analyses do not give unreasonably low weightings to certain inputs or outputs. In this paper we extend the use of reducing weight flexibility and use it to model the effects of the decision-making unit's objectives on its efficiency relative to other DMUs with possibly different objectives. We show how such an approach can identify situations in which the weights imputed by a data envelopment analysis can be inconsistent with the decision-making weights used by the firm, and how this approach can be used to provide efficiency measures that are consistent with the DMU's own objectives. The method allows the analyst to distinguish between a decision-making unit's technological inefficiency and its inability to implement its own policies.     

Microlocal Analysis of Generalized Pullbacks of?Colombeau Functions

In distribution theory the pullback of a general distribution by a C ^∞-function is well-defined whenever the normal bundle of the C ^∞-function does not intersect the wave front set of the distribution. However, the Colombeau theory of generalized functions allows for a pullback by an arbitrary c-bounded generalized function. It has been shown in previous work that in the case of multiplication of Colombeau functions (which is a special case of a C ^∞ pullback), the generalized wave front set of the product satisfies the same inclusion relation as in the distributional case, if the factors have their wave front sets in favorable position. We prove a microlocal inclusion relation for the generalized pullback (by a c-bounded generalized map) of Colombeau functions. The proof of this result relies on a stationary phase theorem for generalized phase functions, which is given in the Appendix. Furthermore we study an example (due to Hurd and Sattinger), where the pullback function stems from the generalized characteristic flow of a partial differential equation.      

Truncated Newton-Based Multigrid Algorithm for Centroidal Voronoi Diagram Calculation

In a variety of modern applications there arises a need to tessellate the domain into representative regions, called Voronoi cells. A particular type of such tessellations, called centroidal Voronoi tessellations or CVTs, are in big demand due to their optimality properties important for many applications. The availability of fast and reliable algorithms for their construction is crucial for their successful use in practical settings. This paper introduces a new multigrid algorithm for constructing CVTs that is based on the MG/Opt algorithm that was originally designed to solve large nonlinear optimization problems. Uniform convergence of the new method and its speedup comparing to existing techniques are demonstrated for linear and nonlinear densities for several 1d and 2d problems, and $O(k)$ complexity estimation is provided for a problem with $k$ generators.     

Separation of Edges in X-Ray Images by Microlocal Analysis

In many x-ray images, we find crossing structures, for example the rib bones of a thorax image. Hence, many edges in such images intersect with other edges. We propose a new algorithm, which simultaneously detects and separates such crossing edges. We prove the functionality of the algorithm under the geometric assumption that the edges possess different orientations at the points of intersection. To this end, we model edges as singularities of distributions with a submanifold structure and define the edge orientation to be the orientation of the corresponding singularity in the sense of microlocal analysis. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

求解圆锥规划的光滑牛顿法

圆锥规划是一类重要的非对称锥优化问题.基于一个光滑函数,将圆锥规划的最优性条件转化成一个非线性方程组,然后给出求解圆锥规划的光滑牛顿法.该算法只需求解一个线性方程组和进行一次线搜索.运用欧几里得约当代数理论,证明该算法具有全局和局部二阶收敛性.最后数值结果表明算法的有效性.