采用BP神经网络记忆模糊规则的控制

本文提供了一种比模糊推理更为自然的方式使用人们的经验知识,通过一组神经元不同 程度的兴奋表达一个抽象的概念值,由此将抽象的经验规则转化成多层神经网络的输入一输 出样本.通过Back-Propagation学习算法使得网络记忆这些样本.控制器以"联想记忆"方 式使用这些经验.本文介绍了控制器的构造方法,给出了控制仿真结果,并讨论了这种控制器 的特点和发展前途.     

An analog circuit design environment based on cooperating blackboard systems

A novel approach to design automation for analog circuits is presented. The prototype implementation-OASE-has been realized as a set of cooperating expert systems with blackboard architecture. The circuit specific knowledge bases use hybrid representation schemes and are strictly separated from an execution engine containing the necessary control knowledge. This alleviates the knowledge acquisition process as well as the extension and maintenance of existing knowledge. OASE has been developed as a design assistant, featuring different levels of interactivity, a hierarchical design style and fully embedded algorithmic standard tools. In its current version it is able to design a broad range of different CMOS operational amplifiers.     

基于地理信息系统的天津房地产管理数据库

从地理信息系统CIS的组成开始．提出该类系统的组织与管理方法，同时重点介绍了在现阶段开发该类系统时所使用的高端技术，最后对GIS系统的发展趋势作出分析与顶测。     

在UNIX工作站上实现SYBASE数据库的空间扩展

七号信令网管系统的数据库服务器采用惠普UNIX工作站及SYBASE数据库。由于采集的数据量增大，原先设计的数据库空间不能满足数据存储三个月的要求．因此采用一块外置硬盘对数据库空间进行扩展。详细地介绍了SYBASE数据库空间扩展的全过程。     

智能电动机控制器在电收尘通风机上的应用

对智能电动机控制器的情况作了介绍，结合工作实践提出了维护要点和建议，并对该控制器的参数设置进行了说明，这对使用该设备的工业企业有一定的指导意义。     

DCOP FOR SMART HOMES: A CASE STUDY

The aim of this article is to bring forth the issue of integrating the services provided by intelligent artifacts in Ambient Intelligence applications. Specifically, we propose a Distributed Constraint Optimization procedure for achieving a functional integration of intelligent artifacts in a smart home. To this end, we employ Adopt-N , a state-of-the-art algorithm for solving Distributed Constraint Optimization Problems (DCOP). This article attempts to state the smart home coordination problem in general terms, and provides the details of a DCOP-based approach by describing a case study taken from the RoboCare project. More specifically, we show how (1) DCOP is a convenient metaphor for casting smart home coordination problems, and (2) the specific features which distinguish Adopt-N from other algorithms for DCOP represent a strong asset in the smart home domain.     

蓝牙智能车载卡的软件实现

介绍一个具有蓝牙通信功能的小型嵌入式系统--蓝牙智能车载卡的软件实现方案.描述了蓝牙智能车载卡在车辆信息化管理系统中的应用,介绍了蓝牙智能车载卡的系统设计方案,重点是软件设计和实现,分析了软件开发中遇到的一些问题及其解决方法,最后给出了实测结果,指出存在的不足之处和改进目标.     

Similarity retrieval of iconic image database

The perception of spatial relationships among objects in a picture is one of the important selection criteria to discriminate and retrieve the images in an iconic image database system. The data structure called 2D string, proposed by Chang et al., is adopted to represent symbolic pictures. The 2D string preserves the objects' spatial knowledge embedded in images. Since spatial relationship is a fuzzy concept, the capability of similarity retrieval for the retrieval by subpicture is essential. In this paper, similarity measure based on 2D string longest common subsequence is defined. The algorithm for similarity retrieval is also proposed. Similarity retrieval provides the iconic image database with the distinguishing function different from a conventional database.     

Data Squashing by Empirical Likelihood

Data squashing was introduced by W. DuMouchel, C. Volinsky, T. Johnson, C. Cortes, and D. Pregibon, in Proceedings of the 5th International Conference on KDD (1999). The idea is to scale data sets down to smaller representative samples instead of scaling up algorithms to very large data sets. They report success in learning model coefficients on squashed data. This paper presents a form of data squashing based on empirical likelihood. This method reweights a random sample of data to match certain expected values to the population. The computation required is a relatively easy convex optimization. There is also a theoretical basis to predict when it will and won't produce large gains. In a credit scoring example, empirical likelihood weighting also accelerates the rate at which coefficients are learned. We also investigate the extent to which these benefits translate into improved accuracy, and consider reweighting in conjunction with boosted decision trees.