Uniform Generation of Binary Trees in Parallel

An unbiased random generator for binary trees is developed for a CREW-PRAM. The generator is capable of generating a binary tree on n nodes in time O(log n), space O(n), with O(n) processors; it is also capable of generating various related combinatorial objects.     

一种挖掘XML文档频繁子树的方法

本文主要研究从由带标签有序树构成的森林中挖掘嵌入式频繁子树,具体做法是：首先对XML文档进行预处理,生成最简结构树SST,然后从SST中挖掘出频繁子树。本文提出了SSTMiner算法,该算法针对TreeMiner算法存在的瓶颈问题,结合当前所处理的SST的结构特点进行改进,进一步提高了算法执行的效率。实验证明,本文提出的方法能够准确高效地
地挖掘出XML文档中的频繁子树。     

A Unified Approach to the Parallel Construction of Search Trees

We present a unified parallel algorithm for constructing various search trees. The tree construction is based on a unified scheme, called bottom-level balancing, which constructs a perfectly balanced search tree having a uniform distribution of keys. The algorithm takes O(log log N) time using N/log log N processors on the EREW PRAM model, and O(1) time with N processors on the CREW PRAM model, where N is the number of keys in the tree.     

一个新的二叉树的轮廓线索树构造算法

本文给出了二叉树的轮廓线索树的一个新的构造算法 .与 Reingdd的算法相比 ,该算法简单、高效、便于分析 ,易于推广到 m-叉树的轮廓线索树的构造算法上     

一种新的决策树分裂属性选择方法

分类问题是数据挖掘和机器学习中的一个核心问题。为了得到最大程度的分类准确率,决策树分类过程中,非常关键的是结点分裂属性的选择。常见的分裂结点属性选择方法可以分为信息熵方法、GINI系数方法等。分析了目前常见的选择分裂属性方法——基于信息熵方法的优、缺点,提出了基于卡方检验的决策树分裂属性的选择方法,用真实例子和设置模拟实验说明了文中算法的优越性。实验结果显示文中算法在分类错误率方面好于以信息熵为基础的方法。     

一种新的决策树分裂属性选择方法

分类问题是数据挖掘和机器学习中的一个核心问题.为了得到最大程度的分类准确率,决策树分类过程中,非常关键的是结点分裂属性的选择.常见的分裂结点属性选择方法可以分为信息熵方法、GINI系数方法等.分析了目前常见的选择分裂属性方法--基于信息熵方法的优、缺点,提出了基于卡方检验的决策树分裂属性的选择方法,用真实例子和设置模拟实验说明了文中算法的优越性.实验结果显示文中算法在分类错误率方面好于以信息熵为基础的方法.     

A Steady State Analysis of Diffracting Trees

Diffracting trees are an effective and highly scalable distributed- parallel technique for shared counting and load balancing. This paper presents the first steady-state combinatorial model and analysis for diffracting trees, and uses it to answer several critical algorithmic design questions. Our model is simple and sufficiently high level to overcome many implementation-specific details, and yet as we show it is rich enough to predict empirically observed behaviors accurately. As a result of our analysis we were able to identify starvation problems in the original diffracting tree algorithm and modify it to a create a more stable version. We were also able to identify the range in which the diffracting tree performs most efficiently, and the ranges in which its performance degrades. We believe our model and modeling approach open the way to steady-state analysis of other distributed-parallel structures such as counting networks and elimination trees. Received October 1996, and in final form July 1997.     

基于校验子的Turbo码编译码原理

在Turbo码的编译码过程中,为了降低计算码字的复杂度,减少在公共信道中信息的泄露,采用一种计算Turbo码字的新的方法,即利用离散变量的线性卷积和二进制解卷积的方法完成Turbo码的码字生成。在译码过程中,使用了校验子和边信息联合的译码方式,使得信息在公共信道中得以保护和约束。仿真结果表明,可分别在信噪比1dB的条件下实现100000个二进制序列的误码率达到了10-4以下。     

PAL信号的亚奈奎斯特压缩编码的混叠消除

高清晰度数字电视（ＨＤＴＶ）对ＰＡＬ彩色全电视信号采用４ｆｓｃ抽样,其数码率４２５．６２７４Ｍｂｉｔ／ｓ。在编码端对其采用２ｆｓｃ亚奈奎斯特压缩编码,可将传送码率压缩一半;在接收端,由解码器将２ｆｓｃ亚奈奎斯特压码插值还原为４ｆｓｃ转化为２ｆｓｃＰＡＬ彩色全电视数字信号的亚奈奎斯特压缩编码的频谱结构,建立了在发送端编码器和接收端解码器的电路模型;研究了对应混叠区的特定形状梳状滤波器对突变图像亮度信     

Contracting Graphs to Paths and Trees

Vertex deletion and edge deletion problems play a central role in parameterized complexity. Examples include classical problems like Feedback Vertex Set, Odd Cycle Transversal, and Chordal Deletion. The study of analogous edge contraction problems has so far been left largely unexplored from a parameterized perspective. We consider two basic problems of this type: Tree Contraction and Path Contraction. These two problems take as input an undirected graph G on n vertices and an integer k, and the task is to determine whether we can obtain a tree or a path, respectively, by a sequence of at most k edge contractions in G. For Tree Contraction, we present a randomized 4 ^k ? n ^O(1) time polynomial-space algorithm, as well as a deterministic 4.98 ^k ? n ^O(1) time algorithm, based on a variant of the color coding technique of Alon, Yuster and Zwick. We also present a deterministic 2 ^k+o(k)+n ^O(1) time algorithm for Path Contraction. Furthermore, we show that Path Contraction has a kernel with at most 5k+3 vertices, while Tree Contraction does not have a polynomial kernel unless NP ? coNP/poly. We find the latter result surprising because of the connection between Tree Contraction and Feedback Vertex Set, which is known to have a kernel with 4k ² vertices.     

A Nonlinear Integral Defined on Partition and its Application to Decision Trees

Nonlinear integrals play an important role in information fusion. So far, all existing nonlinear integrals of a function with respect to a set function are defined on a subset of a space. In many of the problems with information fusion, such as decision tree generation in inductive learning, we often need to deal with the function defined on a partition of the space. Motivated by minimizing the classification information entropy of a partition while generating decision trees, this paper proposes a nonlinear integral of a function with respect to a nonnegative set function on a partition, and provides the conclusion that the sum of the weighted entropy of the union of several subsets is not less than the sum of the weighted entropy of a single subset. It is shown that selecting the entropy of a single attribute is better than selecting the entropy of the union of several attributes in generating rules by decision trees.     

排序算法综述

排序在数据处理中占有极重要的位置，排序算法的好坏，直接影响到实现的复杂度。本文介绍了常用的排序算法，并详细讨论了各种排序法的实现、改进和时间复杂度。最后对这些排序算法进行了比较。     

A Paradigm for Dynamic Coordination of Multiple Robots

In this paper, we present a paradigm for coordinating multiple robots in the execution of cooperative tasks. The basic idea in the paper is to assign to each robot in the team, a role that determines its actions during the cooperation. The robots dynamically assume and exchange roles in a synchronized manner in order to perform the task successfully, adapting to unexpected events in the environment. We model this mechanism using a hybrid systems framework and apply it in different cooperative tasks: cooperative manipulation and cooperative search and transportation. Simulations and real experiments demonstrating the effectiveness of the proposed paradigm are presented.     

排序算法综述

排序在数据处理中占有极重要的位置,排序算法的好坏,直接影响到实现的复杂度。本文介绍了常用的排序算法,并详细讨论了各种排序法的实现、改进和时间复杂度。最后对这些排序算法进行了比较。     

Virtually Documented Environments: A New Interface Paradigm for Task-oriented Access to Information

We present a suitable virtually documented environment system providing the user with high level interaction possibilities. The system is dedicated to applications where the operator needs to have his hands free in order to access information, carry out measurements and/or operate on a device (e.g. maintenance, instruction). The system merges video images acquired through a head-mounted video camera with synthetic data (multimedia documents including CAD models and text) and presents these merged images to the operator. Registration techniques allow the operator to visualise information properly correlated to the real world: this is an essential aspect in order to achieve a feeling of presence in a real environment. We increase the sense of immersion through high level Human-Computer Interaction (HCI) allowing hands-free access to information through vocal commands as well as multimodal interaction associating speech and gesture. In this way, the user can access information and manipulate it in a very natural manner. We discuss the construction of the documentation system and the requested functionalities which led to the system architecture.     

一种融合程序员和神经网络的自动化程序生成方法

程序生成是人工智能的核心研究问题之一, 当前输入-输出样例驱动的神经网络模型是非常流行的研究方法.面临的主要挑战是泛化能力差、生成程序准确率保证、难以处理复杂程序结构(如分支、循环、递归等), 主要原因是模型的输入信息单一(输入-输出对)和完全依赖神经网络.显然单一地通过输入输出样例倒推程序行为存在歧义性, 而神经网络的记忆容量很难满足常规程序的变量存储需求.提出一种人工与神经网络生成相协作的编程模型, 融合神经网络和程序员各自的优势, 其中程序员用高级编程语法编写程序框架, 神经网络自动学习生成程序局部的琐碎细节, 从而促进自动化程序生成方法更好地应对实际应用挑战.实验表明, 研究方法是有效的, 跟同类代表性研究方法相比表现出更好的学习性能.     

基于快速成型原理的实物模型制作系统

模型是制图教学中不可缺少的教具,虚拟模型易于创建而实物模型的真实感更强,二者在目前的教学中均发挥着重要的作用。但遗憾的是,观摩这些现成的模型对学生来说是被动的认知,其效果远远不及引导学生自己来制作实物模型。论文介绍了一种基于快速成型原理的实物模型制作系统,利用一台电脑和打印机便可以快速、低成本地制作出各种复杂的模型。制作模型的实践环节不仅能够激发学生的学习兴趣,还能够促进学生对截切、辅助平面法和剖切等难点、重点内容的理解和掌握。     

一种全局统一的层次化网格资源模型

网格计算通过新的组织方式将广域网上的各种计算资源、信息资源、设备资源等集成起来，以统一的方式向用户提供服务，是当前网络计算领域的研究热点，引入逻辑资源树的概念，通过抽象资源参数，提出了一种全局统一的层次化网格资源模型，支持资源的动态加入与删除，与资源池及全局一本地两层资源模型相比，提出的资源模型有效地屏蔽了广域网上资源的异构性，提高了资源的可扩展性；同时根据网络通信性能对资源进行层次化组织，避免了盲目的资源选择，该模型进行资源查找的时间复杂度为Olog(N)，有较高的查找效率。