移动式宽频带高产额中子发生器

多用途中子发生器有着广阔的市场和应用领域 ,文章对移动式宽频带高产额中子发生器 ,在设计制造过程中所涉及到的技术难点 :绝缘尺寸小、频率适应范围宽、为中子管提供靶压的高压负载特性好等作了技术分析 ,使多用途中子发生器在更广阔的范围内应用 ,提供了广阔前景。     

单片机仿真系统

本文讨论单片机离线仿真系统的设计方法，其关键技术是：单片机硬件系统（ＲＡＭＲＥＧＩＳＴＥＲＳ）仿真，指令系统仿真，中断系统仿真，应用系统硬件仿真。     

参数化图形库技术

本文论述了参数化图形库的实现原理，建立了以尺寸叠加算法为基础的参数化图形库开发工具，利用这种开发工具建立的图形数据可以由数据库管理，方便有效。     

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。     

Partitioned encoding schemes for algorithm-based fault tolerance inmassively parallel systems

Considers the applicability of algorithm based fault tolerance (ABET) to massively parallel scientific computation. Existing ABET schemes can provide effective fault tolerance at a low cost For computation on matrices of moderate size; however, the methods do not scale well to floating-point operations on large systems. This short note proposes the use of a partitioned linear encoding scheme to provide scalability. Matrix algorithms employing this scheme are presented and compared to current ABET schemes. It is shown that the partitioned scheme provides scalable linear codes with improved numerical properties with only a small increase in hardware and time overhead     

Weight smoothing to improve network generalization

A weight smoothing algorithm is proposed in this paper to improve a neural network's generalization capability. The algorithm can be used when the data patterns to be classified are presented on an n-dimensional grid (n>/=1) and there exists some correlations among neighboring data points within a pattern. For a fully-interconnected feedforward net, no such correlation information is embedded into the architecture. Consequently, the correlations can only be extracted through sufficient amount of network training. With the proposed algorithm, a smoothing constraint is incorporated into the objective function of backpropagation to reflect the neighborhood correlations and to seek those solutions that have smooth connection weights. Experiments were performed on problems of waveform classification, multifont alphanumeric character recognition, and handwritten numeral recognition. The results indicate that (1) networks trained with the algorithm do have smooth connection weights, and (2) they generalize better.     

Network information criterion-determining the number of hiddenunits for an artificial neural network model

The problem of model selection, or determination of the number of hidden units, can be approached statistically, by generalizing Akaike's information criterion (AIC) to be applicable to unfaithful (i.e., unrealizable) models with general loss criteria including regularization terms. The relation between the training error and the generalization error is studied in terms of the number of the training examples and the complexity of a network which reduces to the number of parameters in the ordinary statistical theory of AIC. This relation leads to a new network information criterion which is useful for selecting the optimal network model based on a given training set.     

Hierarchical models for analysis and recognition of handwritten characters

Different hierarchical models in pattern analysis and recognition are proposed, based on occurrence probability of patterns. As an important application of recognizing handprinted characters, three typical kinds of hierarchical models such asM _89-89,M _89-36 andM _36-36 have been presented, accompanied by the computer algorithms for computing recognition rates of pattern parts. Moreover, a comparative study of their recognition rates has been conducted theoretically; and numerical experiments have been carried out to verify the analytical conclusions made. Various hierarchical models deliberated in this paper can provide users more or better choices of pattern models in practical application, and lead to a uniform computational scheme (or code). The recognition rates of parts can be improved remarkably by a suitable hierarchical model. For the modelM _89-36 in which case some of the Canadian standard handprinted characters have multiple occurrence probabilities, the total mean recognition rates of the given sample may reach 120% of that by the model proposed by Li et al., and 156% of that obtained from the subjective experiments reported by Suen.     

Pipelining and bypassing in a VLIW processor

This short note describes issues involved in the bypassing mechanism for a very long instruction word (VLIW) processor and its relation to the pipeline structure of the processor. The authors first describe the pipeline structure of their processor and analyze its performance and compare it to typical RISC-style pipeline structures given the context of a processor with multiple functional units. Next they study the performance effects of various bypassing schemes in terms of their effectiveness in resolving pipeline data hazards and their effect on the processor cycle time     

Second-order bounds on the domain of attraction and the rate ofconvergence of nonlinear dynamical systems and neural networks

We present a method for analyzing the convergence properties of nonlinear dynamical systems yielding second-order bounds on the domain of attraction of an asymptotically stable equilibrium point and on the time of convergence in the estimated domain. We show that under certain conditions on the system, there exists an analytic solution to the corresponding optimization problem. The method is applied in analyzing the dynamics of a neural network model.