Development of a recurrent Sigma-Pi neural network rainfall forecasting system in Hong Kong

At the moment, weather forecasting is still an art — the experience and intuition of forecasters play a significant role in determining the quality of forecasting. This paper describes the development of a new approach to rainfall forecasting using neural networks. It deals with the extraction of information from radar images and an evaluation of past rain gauge records to provide shortterm rainfall forecasting. All of the meteorological data were provided by the Royal Observatory of Hong Kong (ROHK). Preprocessing procedures were essential for this neural network rainfall forecasting. The forecast of the rainfall was performed every half an hour so that a storm warning signal can be delivered to the public in advance. The network architecture is based on a recurrent Sigma-Pi network. The results are very promising, and this neural-based rainfall forecasting system is capable of providing a rain storm warning signal to the Hong Kong public one hour ahead.     

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.     

光纤通信在市内接入网的应用

先说明市内接入网的单位用户和住家用户两大类使用通信和电视、交互型和分配型业务的要求不相同，相应地对光纤传输的应用须作不同的考虑，文中认为；光纤从市内交换局直连办公大楼是合乎现实需要的，而对于居民住家，宜选用光纤连至路边或光纤与同轴结合和适当利用无源光网络等方案，俟将来时机成熟才实行光纤连至每一家，文末有概括总结，说明接入网不同于长途网，接入网的光纤系统可以使用常规单模光纤，工作于波长1．3μm，而光放大器和波分多路系统不是普遍需要，但光电子集成在光端机中是必要的。     

高氧化态（Ⅱ─Ⅳ）三核金属簇合物构型的人工神经网络判别方法

本文运用一典型的人工神经网络模型─“反向传播”模型，对高氧化态（Ⅱ─Ⅳ）三核金属簇合物的构型分布进行了分析，得到了较好的分类、预报结果为化合物结构分析提供了新的工具。     

Windows系统中两种动态交换数据的方法

本文介绍了Ｗｉｎｄｏｗｓ环境下基于消息的ＤＤＥ和基于动态链接库的ＤＤＥＭＬ的区别，并详细叙述了如何使用ＤＤＥＭＬ编制Ｗｉｎｄｏｗｓ应用程序。     

Statistical synchronization among participants in real-time multimedia conferencing

In this paper, an algorithm to determine the set of packets generated continuously and periodically from different participants that are arriving at a node either for mixing at the master of a conference, or for simply playing back at a regular participant of a conference, is proposed. The essence of the algorithm is to estimate the expected packet arrival time (or reference time) for each participant. With the reference time at hand, the maximum jitter and the optimum waiting time for a mixer to wait packets from all participants can be determined. An enhancement to improve synchronization which deals with the estimation of the time offsets between the individual periods of the sources and the period of the receiver is also presented. The error of the proposed algorithm is enumerated by the Chernoff bound and demonstrated by simulation and is shown to be acceptable in practical application. The algorithm can also be employed when traffic sources operate with different periods.     

A formal description of open distributed processing (ODP) trading based on guidelines for the definition of managed objects (GDMO)

New requirements of growing computer networks and information systems have an influence on extended client/server models with increased functionality. This forms the basis for service management in distributed systems which is realized by a service trading concept. This paper studies the requirements derived from the Open Distributed Processing (ODP) Reference Model in order to consider an open service market. Furthermore, it examines management possibilities for describing the service trading scenario. Because of similar architectures and properties ODP services, service offers, types, exporters and traders are mapped onto management components and modeled as managed objects. Therefore, the Guidelines for the Definition of Managed Objects (GDMO) are used. The final concept allows a precise and unambiguous study of the service trading scenario and provides means for exporting and importing of service offers in a distributed environment.     

井场信息系统建设体系结构

对井场钻井数据实时远程传输的研究和实践进行了总结,从数据远传作用、数据远传通信方式、数据通信网络体系结构、未来发展等几个方面对井场数据远程传输进行了探讨。     

Mixed Mode VLSI Implementation of a Neural Associative Memory

A mixed mode digital/analog special purpose VLSI hardware implementation of an associative memory with neural architecture is presented. The memory concept is based on a matrix architecture with binary storage elements holding the connection weights. To enhance the processing speed analog circuit techniques are applied to implement the algorithm for the association. To keep the memory density as high as possible two design strategies are considered. First, the number of transistors per storage element is kept to a minimum. In this paper a circuit technique that uses a single 6-transistor cell for weight storage and analog signal processing is proposed. Second, the device precision has been chosen to a moderate level to save area as much as possible. Since device mismatch limits the performance of analog circuits, the impact of device precision on the circuit performance is explicitly discussed. It is shown that the device precision limits the number of rows activated in parallel. Since the input vector as well as the output vector are considered to be sparsely coded it is concluded, that even for large matrices the proposed circuit technique is appropriate and ultra large scale integration with a large number of connection weights is feasible.     

COATES GRAPH APPROACH FOR GENERATING SYMBOLIC NETWORK FUNCTION

In this paper, symbolic code matrix ,constant matrix and count matrix are defined .The first twomatrices are used to describe the elemental expression of augmented matrix and the nede admittance equa-tion is thus obtained. The third matrix is used to obtain the incoming degree matrix, and according to thematrix all the 1- factors of the Coates graph are given. By using the data code, the determinant is expandedand the same items in the expansion are merged. Thus the symbolic network function in which no term can-cellation occurs is generated.