高速贴片机优化软件的设计与开发

SMT生产线要达到最大的产量,必须要考虑生产线的效率。贴片机是SMT生产线中的关键设备,因此提高贴片机的生产效率具有十分重要的意义。本文以松下贴片机为例,介绍了贴片机程序优化软件的设计与开发中的思想、方法和经验,希望对从事CAM软件研究的工程人员有一定帮助。     

基于有限状态的全周期序列混沌映射的研究

在有限长度的数字计算机中，混沌迭代序列是一个有限周期序列，其相关性能远远低于理想序列。基于skew tent映射，提出一种离散化的有限状态混沌映射，它允许精确的数值计算，没有舍入误差，通过选择合适的参数，映射能产生全周期长度的序列。仿真实验表明，归一化的序列平均周期对计算机精度不敏感，生成的二进制序列具有良好的相关性能。     

Evaluation of performance enhancing proxies in internet over satellite

Performance enhancing proxies (PEPs) are widely used to improve the performance of TCP over high delay‐bandwidth product links and links with high error probability. In this paper we analyse the performance of using TCP connection splitting in combination with web caching via traces obtained from a commercial satellite system. We examine the resulting performance gain under different scenarios, including the effect of caching, congestion, random loss and file sizes. We show, via analysing our measurements, that the performance gain from using splitting is highly sensitive to random losses and the number of simultaneous connections, and that such sensitivity is alleviated by caching. On the other hand, the use of a splitting proxy enhances the value of web caching in that cache hits result in much more significant performance improvement over cache misses when TCP splitting is used. We also compare the performance of using different versions of HTTP in such a system. Copyright © 2003 John Wiley & Sons, Ltd.     

Sensitivity analysis of thermal performances of flat plate solar air heaters

Sensitivity analysis is a mathematical tool, first developed for optimization methods, which aim is to characterize a system response through the variations of its output parameters following modifications imposed on the input parameters of the system. Such an analysis may quickly become laborious when the thermal model under consideration is complex or the number of input parameters is high. In this paper, we develop a mathematical model to analyse the heat exchanges in four different types of solar air collectors. When building this thermal model we show that for each collector, at quasi-steady state, the energy balance equations of the components of the collector cascade into a single first-order non-linear differential equation that is able to predict the thermal behaviour of the collector. Our heat transfer model clearly demonstrates the existence of an important dimensionless parameter, referred to as the thermal performance factor of the collector, that compares the useful thermal energy which can be extracted from the heater to the overall thermal losses of that collector for a given set of input parameters. A sensitivity analysis of our thermal model has been performed for the most significant input parameters such as the incident solar irradiation, the inlet fluid temperature, the air mass flow rate, the depth of the fluid channel, the number and nature of the transparent covers in order to measure the impact of each of these parameters on our model. An important result which can be drawn from this study is that the heat transfer model developed is robust enough to be used for thermal design studies of most known flat plate solar air heaters, but also of flat plate solar water collectors and linear solar concentrators.     

热作模具钢表面激光堆焊耐磨合金层的研究

本文主要通过在H13钢上用大功率CO_2激光束进行堆焊,阐述了激光堆焊工艺变化对堆焊组织和性能的影响,在本试验条件下,得到了高密度弥散金属化合物组织的激光堆焊层,平均硬度为HV800,与基体呈冶金结合,耐磨性比H13模具钢提高149%。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Equivalence of variational inequality problems to unconstrained minimization

In this paper we propose a class of merit functions for variational inequality problems (VI). Through these merit functions, the variational inequality problem is cast as unconstrained minimization problem. We estimate the growth rate of these merit functions and give conditions under which the stationary points of these functions are the solutions of VI. This work was supported by the state key project “Scientific and Engineering Computing”.     

k-树的补图的最小填充和树宽

一个图的最小填充问题是寻求边数最少的弦母图,一个图的树宽问题是寻求团数最小的弦母图,这两个问题分别在稀疏矩阵计算及图的算法设计中有非常重要的作用．一个k-树G的补图G称为k-补树．本文给出了k-补树G的最小填充数f(G) 及树宽TW(G)．     

Well-Posedness by Perturbations of Variational Problems

In this paper, we consider the extension of the notion of well-posedness by perturbations, introduced by Zolezzi for optimization problems, to other related variational problems like inclusion problems and fixed-point problems. Then, we study the conditions under which there is equivalence of the well-posedness in the above sense between different problems. Relations with the so-called diagonal well-posedness are also given. Finally, an application to staircase iteration methods is presented.     

BoneRoute: An Adaptive Memory-Based Method for Effective Fleet Management

This paper presents an adaptive memory-based method for solving the Capacitated Vehicle Routing Problem (CVRP), called BoneRoute. The CVRP deals with the problem of finding the optimal sequence of deliveries conducted by a fleet of homogeneous vehicles, based at one depot, to serve a set of customers. The computational performance of the BoneRoute was found to be very efficient, producing high quality solutions over two sets of well known case studies examined.