基于参差距离的相位差变化值的解模糊方法研究

利用相位差及其变化率对辐射源进行定位是新近提出的一种快速单基无源定位方法。本文分析了利用相位干涉议得到的相位差变化值的相位模糊特点,提出了一种利用相位干涉仪的接收天线之间的参差距离对相位差变化值进行解模糊的方法,讨论了正确解模糊的条件和范围,并给出了仿真结果。     

DDS技术在数字激光相位测距仪中的应用

本文介绍了直接数字合成(DDS)技术在激光相位测距仪中的应用。使用该技术研制的数字激光相位测距仪具有操作简便、携带方便、性能可靠的特点，测相精度优于干分之一。     

离轴数字全息记录条件的研究

用振幅全息和菲涅耳衍射理论,分析离轴数字全息记录系统结构参数对数字全息再现的影响,并进行相应的实验验证。理论分析和实验研究结果都表明,如果记录物体和CCD的尺寸固定,记录物体和CCD之间的记录距离将直接影响数字全息再现像的分离状况和系统的分辨率,在保证再现像分离的前提下,缩短物体和CCD之间的距离将有利于数字全息再现像分辨率的提高。     

运用模式分类的雷达抗转发式距离欺骗干扰方法

针对雷达转发式欺骗干扰中的距离欺骗，提出了一种基于模式分类来识别目标与干扰的方法。该方法基于干扰和目标能量和起伏特性差异确定提取特征因子，再利用RBF神经网络方法进行分类。仿真结果表明，该方法具有较好的抗距离欺骗干扰性能。     

Decomposition algorithms for the tree edit distance problem

We study the behavior of dynamic programming methods for the tree edit distance problem, such as [P. Klein, Computing the edit-distance between unrooted ordered trees, in: Proceedings of 6th European Symposium on Algorithms, 1998, p. 91–102; K. Zhang, D. Shasha, SIAM J. Comput. 18 (6) (1989) 1245–1262]. We show that those two algorithms may be described as decomposition strategies. We introduce the general framework of cover strategies, and we provide an exact characterization of the complexity of cover strategies. This analysis allows us to define a new tree edit distance algorithm, that is optimal for cover strategies.     

Tomography of Binomial States of the Radiation Field

The symplectic, optical, and photon-number tomographic symbols of binomial states of the radiation field are studied. Explicit relations for all tomograms of the binomial states are obtained. Two measures for nonclassical properties of these states are discussed.     

Construction of best Bregman approximations in reflexive Banach spaces

An iterative method is proposed to construct the Bregman projection of a point onto a countable intersection of closed convex sets in a reflexive Banach space.

     

Structural properties and tractability results for linear synteny

The syntenic distance between two species is the minimum number of fusions, fissions, and translocations required to transform one genome into the other. The linear syntenic distance, a restricted form of this model, has been shown to be close to the syntenic distance. Both models are computationally difficult to compute and have resisted efficient approximation algorithms with non-trivial performance guarantees. In this paper, we prove that many useful properties of syntenic distance carry over to linear syntenic distance. We also give a reduction from the general linear synteny problem to the question of whether a given instance can be solved using the maximum possible number of translocations. Our main contribution is an algorithm exactly computing linear syntenic distance in nested instances of the problem. This is the first polynomial time algorithm exactly solving linear synteny for a non-trivial class of instances. It is based on a novel connection between the syntenic distance and a scheduling problem that has been studied in the operations research literature.     

A strong law of large numbers for generalized random sets from the viewpoint of empirical processes

In this article we prove a strong law of large numbers for Borel measurable nonseparably valued random elements in the case of generalized random sets.

     

Minimum Disparity Estimation in Linear Regression Models: Distribution and Efficiency

This paper deals with the minimum disparity estimation in linear regression models. The estimators are defined as statistical quantities which minimize the blended weight Hellinger distance between a weighted kernel density estimator of errors and a smoothed model density of errors. It is shown that the estimators of the regression parameters are asymptotic normally distributed and efficient at the model if the weights of the density estimators are appropriately chosen.