基于信道缩短的TH-PPM UWB稀疏信道盲估计算法

针对TH-PPM UWB系统,提出一种基于信道缩短的UWB稀疏信道盲估计算法.该算法通过对接收信号进行信道缩短,有效地克服了信道过长给估计精度带来的影响.同时利用UWB信道的稀疏簇特性,避免了无谓的零值抽头估计,改善了该算法的性能.仿真结果表明:当信道长度大于符号长度时,该算法可以获得较好的估计性能.     

论图像色彩模式及其之间的转换

色彩模式是指在电脑中颜色的不同组合方式,不同的色彩模式有不同的特性,也可以进行互相交换。本文就图像常见的三种色彩模式之间何时进行转换做了较为详细的论述。论述从图像的编辑和印刷方面展开,帮助用户解决何时何地应该用何种图像色彩模式。     

高校档案数字化实践中的思考

档案数字化是信息时代对于档案工作的新要求,推进档案数字化建设也是高校信息化工程中的一项基础性工作。档案数字化工作给予了档案人新的使命和机遇,然而在实际工作中也存在很多问题和困难。本文就高校档案数字化实践中存在的若干问题以及我们的思考探索做了阐述。     

基础软件技术的发展趋势

从分析基础软件的基本概念和特性出发,对基础软件的内容、需求、技术、产品等方面进行了系统论述。探讨了现有的主流开发技术及未来的发展趋势。通过分析现有部分国产软件系统在一些典型领域的应用,揭示我国基础软件发展的现状和难题,为现有国产基础软件产业的发展提供决策参考。     

ARP病毒的分析与防护

现代化的办公系统往往都离不开对电脑的使用,企业和部门电脑运行的稳定尤为重要,由于人们为对电脑的使用不当,或是信息管理部门的管理疏忽,使我们的网络经常受到电脑病毒的干扰,特别是常见的ARP病毒,比如聚生网管、P2P终结者、网络执法官、网络剪刀手、局域网终结者等。ARP病毒通常表现为网络传播快,感染终端定位困难等特点,一旦感染就导致大面积的计算机终端无法进行网络访问     

浅谈政府公文交换系统的发展

在社会信息化的不断推进过程中,各级政府的办公自动化需求也在不断升级,公文交换系统多样化且技术更新加速,随着改革的深入和我国加入WTO,公文交换系统的建设已经成为当前我国信息化建设的首要任务.     

基于Web_CORBA信息家电家庭网关的设计与实现

随着各种信息家电的出现及网络技术的发展,家电控制需要一个便捷有效的平台。本文提出了Web_CORBA家庭网关的设计构想,给出了信息家电的接口定义,采用CORBA-CGI方式最终实现了Internet远程控制,并以信息家电冰箱为例给出了具体的设计过程。     

Optimally Adaptive Integration of Univariate Lipschitz Functions

We consider the problem of approximately integrating a Lipschitz function f (with a known Lipschitz constant) over an interval. The goal is to achieve an additive error of at most ε using as few samples of f as possible. We use the adaptive framework: on all problem instances an adaptive algorithm should perform almost as well as the best possible algorithm tuned for the particular problem instance. We distinguish between and , the performances of the best possible deterministic and randomized algorithms, respectively. We give a deterministic algorithm that uses samples and show that an asymptotically better algorithm is impossible. However, any deterministic algorithm requires samples on some problem instance. By combining a deterministic adaptive algorithm and Monte Carlo sampling with variance reduction, we give an algorithm that uses at most samples. We also show that any algorithm requires samples in expectation on some problem instance (f,ε), which proves that our algorithm is optimal.     

Path Hitting in Acyclic Graphs

An instance of the path hitting problem consists of two families of paths, and ℋ, in a common undirected graph, where each path in ℋ is associated with a non-negative cost. We refer to and ℋ as the sets of demand and hitting paths, respectively. When p∈ℋ and share at least one mutual edge, we say that p hits q. The objective is to find a minimum cost subset of ℋ whose members collectively hit those of . In this paper we provide constant factor approximation algorithms for path hitting, confined to instances in which the underlying graph is a tree, a spider, or a star. Although such restricted settings may appear to be very simple, we demonstrate that they still capture some of the most basic covering problems in graphs. Our approach combines several novel ideas: We extend the algorithm of Garg, Vazirani and Yannakakis (Algorithmica, 18:3–20, 1997) for approximate multicuts and multicommodity flows in trees to prove new integrality properties; we present a reduction that involves multiple calls to this extended algorithm; and we introduce a polynomial-time solvable variant of the edge cover problem, which may be of independent interest. An extended abstract of this paper appeared in Proceedings of the 14th Annual European Symposium on Algorithms, 2006. This work is part of D. Segev’s Ph.D. thesis prepared at Tel-Aviv University under the supervision of Prof. Refael Hassin.     

Measuring ranked list robustness for query performance prediction

We introduce the notion of ranking robustness, which refers to a property of a ranked list of documents that indicates how stable the ranking is in the presence of uncertainty in the ranked documents. We propose a statistical measure called the robustness score to quantify this notion. Our initial motivation for measuring ranking robustness is to predict topic difficulty for content-based queries in the ad-hoc retrieval task. Our results demonstrate that the robustness score is positively and consistently correlation with average precision of content-based queries across a variety of TREC test collections. Though our focus is on prediction under the ad-hoc retrieval task, we observe an interesting negative correlation with query performance when our technique is applied to named-page finding queries, which are a fundamentally different kind of queries. A side effect of this different behavior of the robustness score between the two types of queries is that the robustness score is also found to be a good feature for query classification.