关于统计学习理论与支持向量机

模式识别、函数拟合及概率密度估计等都属于基于数据学习的问题,现有方法的重 要基础是传统的统计学,前提是有足够多样本,当样本数目有限时难以取得理想的效果.统计 学习理论(SLT)是由Vapnik等人提出的一种小样本统计理论,着重研究在小样本情况下的 统计规律及学习方法性质.SLT为机器学习问题建立了一个较好的理论框架,也发展了一种 新的通用学习算法--支持向量机(SVM),能够较好的解决小样本学习问题.目前,SLT和 SVM已成为国际上机器学习领域新的研究热点.本文是一篇综述,旨在介绍SLT和SVM的 基本思想、特点和研究发展现状,以引起国内学者的进一步关注.  

知识约简的一种启发式算法

知识约简是Ｒｏｕｇｈ Ｓｅｔ理论研究中的核心内容之一，现已证明了寻找决策表的最小约简是ＮＰ－ｈａｒｄ问题，文中首先从信息的角度，对决策表中属性的重要性给出度量；在此基础上，提出了一种基于互信息的知识相对约简的启发式算法，并指出算法的复杂性是多项式的；最后，通过  

工作流技术综述

工作流技术是进入90年代以后计算机应用领域的一个新的研究热点.对工作流技术进行深入的研究对于提高我国企业的信息化程度、运行效率以及竞争能力都有着重要的意义.该文首先介绍了工作流技术的起源与发展;然后对工作流的研究现状进行综述,主要包括工作流定义、工作流模型、工作流实现方案以及工作流事务管理这4个方面;同时分析了目前工作流技术中所存在的不足以及造成这些不足的根本原因;最后指出了工作流技术的未来发展趋势.  

Color indexing

Computer vision is embracing a new research focus in which the aim is to develop visual skills for robots that allow them to interact with a dynamic, realistic environment. To achieve this aim, new kinds of vision algorithms need to be developed which run in real time and subserve the robot's goals. Two fundamental goals are determining the location of a known object. Color can be successfully used for both tasks.This article demonstrates that color histograms of multicolored objects provide a robust, efficient cue for indexing into a large database of models. It shows that color histograms are stable object representations in the presence of occlusion and over change in view, and that they can differentiate among a large number of objects. For solving the identification problem, it introduces a technique calledHistogram Intersection, which matches model and image histograms and a fast incremental version of Histogram Intersection, which allows real-time indexing into a large database of stored models. For solving the location problem it introduces an algorithm calledHistogram Backprojection, which performs this task efficiently in crowded scenes.  

Bagging Predictors

Bagging predictors is a method for generating multiple versions of a predictor and using these to get an aggregated predictor. The aggregation averages over the versions when predicting a numerical outcome and does a plurality vote when predicting a class. The multiple versions are formed by making bootstrap replicates of the learning set and using these as new learning sets. Tests on real and simulated data sets using classification and regression trees and subset selection in linear regression show that bagging can give substantial gains in accuracy. The vital element is the instability of the prediction method. If perturbing the learning set can cause significant changes in the predictor constructed, then bagging can improve accuracy.  

Agent研究现状与发展趋势

对有关Agent理论和实践两方面的研究现状、关键技术和发展趋势进行了综述和讨论，试图勾画出目前Agent研究的脉络、重点及其发展趋向.主要内容包括：（1）智能Agent的特性、表示和推理；（2）多Agent系统的联合意图、协商和规划；（3）面向Agent的程序设计.最后，简单讨论了Agent技术目前所面临的挑战.  

Distinctive Image Features from Scale-Invariant Keypoints

This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. This paper also describes an approach to using these features for object recognition. The recognition proceeds by matching individual features to a database of features from known objects using a fast nearest-neighbor algorithm, followed by a Hough transform to identify clusters belonging to a single object, and finally performing verification through least-squares solution for consistent pose parameters. This approach to recognition can robustly identify objects among clutter and occlusion while achieving near real-time performance.  

计算机视觉中摄像机定标综述

回顾了摄影测量学和计算机视觉中的各种摄像机定标方法,对各种方法进行了分 析、比较、并讨论了摄像机定标方法应用于计算机视觉中的特点.  

PID参数先进整定方法综述

PID控制是过程控制中应用最广泛的控制方法.文中综述了PID参数先进整定方法 及近年来在此方面得到的最新研究成果,并对将来的发展进行了展望.  

云计算:系统实例与研究现状

针对云计算这样一个范畴综述了当前云计算所采用的技术,剖析其背后的技术含义以及当前云计算参与企业所采用的云计算实现方案.云计算包含两个方面的含义:一方面是底层构建的云计算平台基础设施,是用来构造上层应用程序的基础;另外一方面是构建在这个基础平台之上的云计算应用程序.主要是针对云计算的基础架构的研究与实现状况给出综述,对于云计算的应用也有所涉及.云计算有3个最基本的特征:第1个是基础设施架构在大规模的廉价服务器集群之上;第二是应用程序与底层服务协作开发,最大限度地利用资源;第3个是通过多个廉价服务器之间的冗余,通过软件获得高可用性.云计算达到了两个分布式计算的重要目标:可扩展性和高可用性.可扩展性表达了云计算能够无缝地扩展到大规模的集群之上,甚至包含数千个节点同时处理.高可用性代表了云计算能够容忍节点的错误,甚至有很大一部分节点发生失效也不会影响程序的正确运行.通过此文可以了解云计算的当前发展状况以及未来的研究趋势.