Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.     

使用遗传算法的迷宫学习

本文试用遗传计算及决策制定方法来实现机器人有认识迷宫意向的能力，这里“意向”是指遵循对迷宫特有的路径规则所出的决定，令机器人在两个相对的迷宫中行走学习，一个迷宫路径是基于同样的意向，另一个则基于不同的意向，研究结果确认了已达成的意向学习。     

大规模数据库中的知识获取

一、前言数据是知识的潭泉,拥有大量的数据与拥有许多有用的知识完全是两回事.为了有效地利用大量的公共数据,必须更好地理解这些数据,并从其中快速、准确地发现知识.这里所说的知识是指大量数据中存在的规律性(r egularity)或不同属性值之间所存在的[I F THEN〕规则.将所获取的知识附加于仅由事实数据(fact data)构成的传统数据库上,既可强化数据库的查询能力,又可给数据库提供推理能力,     

通信网技术的发展及其市场预测

本文详细地评述了发展通信网所涉及的一些关键技术以及国外通信网的现状和发展趋热;并简要地介绍了我国通信网的发展情况;最后,对通信网市场进行了预测。     

人工关节试验机电液力伺服控制系统迭代学习控制策略仿真

本文首先介绍了人工关节试验机电液力伺服控制系统的构成，并分析了其静特性。针对力系统的特性，本文提出了一种闭环比例型一阶给定超前迭代学习控制算法，并对其控制效果进行了仿真研究。研究结果表明，采用迭代学习控制算法可以有效地提高力系统的跟随精度。     

Design and Implementation of a Flexible Manufacturing Control System Using Neural Network

Design and implementation of a sequential controller based on the concept of artificial neural networks for a flexible manufacturing system are presented. The recurrent neural network (RNN) type is used for such a purpose. Contrary to the programmable controller, an RNN-based sequential controller is based on a definite mathematical model rather than depending on experience and trial and error techniques. The proposed controller is also more flexible because it is not limited by the restrictions of the finite state automata theory. Adequate guidelines of how to construct an RNN-based sequential controller are presented. These guidelines are applied to different case studies. The proposed controller is tested by simulations and real-time experiments. These tests prove the successfulness of the proposed controller performances. Theoretical as well as experimental results are presented and discussed indicating that the proposed design procedure using Elman's RNN can be effective in designing a sequential controller for event-based type manufacturing systems. In addition, the simulation results assure the effectiveness of the proposed controller to outperform the effect of noisy inputs.     

基于分层加权的多边形图形匹配

提出了一种适用凸凹多边形匹配的分层加权测度方法，在此方法中，对凹多边形、首先进行基于提取凸多边形的模式分解，对凹多边形添加辅助线，形成新的外接凸多边形、通过依次抽取外接凸多边形，将凹多边形表达为仅由凸多边形组成的多层拓扑结构，然后，利用预先定义的互为模板的相似度量准则和分层加权测度模型，计算得到多边形的相似度系数，从而实现凹多边形的匹配和检索。     

在协议集成测试系统上开展路由协议测试

在分析路由协议的特性及其测试需求的基础上，提出利用窗口黑盒来描述被测协议，利用多通道测试方法扩展对被测实现的控制和观察，通过扩充参考实现增强系统的测试能力。将这些理论，技术应用于系统中，对路由协议开展了有效的测试活动，为国产高性能路由器的开发提供了有力的支持，也进一步增强了PITS系统的功能和适用性。     

FILIP: A fuzzy intelligent information system with learning capabilities

FILIP (fuzzy intelligent learning information processing) system is designed with the goal to model human information processing. The issues addressed are uncertain knowledge representation and approximate reasoning based on fuzzy set theory, and knowledge acquisition by “being told” or by “learning from examples”. Concepts that can be “learned” by the system can be imprecise (fuzzy), or the knowledge can be incomplete. In the latter case, FILIP uses the concept of similarity to extrapolate the knowledge to cases that were not covered by examples provided by the user. Concepts are stored in the Knowledge Base and employed in intelligent query processing, based on flexible inference that supports approximate matches between the data in the database and the query.

The architecture of FILIP is discussed, the learning algorithm is described, and examples of the system's performance in the knowledge acquisition and querying modes, together with its explanatory capabilities are shown.     

一种以太网兼容的综合话音/数据传输协议

本文提出一种与现有以太网兼容的综合话音/数据协议.描述了协议模型及实现方法.并用PASCAL语言在IBM-PC机上模拟研究了该协议的性能.模拟结果表明,该协议能满足话音的实时要求,性能良好,且数据传输性能没有明显下降.协议克服了以太网传输话音延迟不确定的缺点.