低空大气对连续波干涉仪系统相位稳定性的影响

针对三站连续波干涉仪系统，根据实时测得的系统场区大气折射率漂移数据，应用几何光学方法，从理论上估计了连续波干波仪系统两条微波基线传输的相位稳定性。     

基于Matlab的线性规划问题求解

线性规划是运筹学中研究较早、发展较快、应用广泛、方法成熟的一个重要分支,它是辅助人们进行科学管理的一种重要的数学方法.文章首先介绍了线性规划的基本概念及标准形式,着重讨论了线性规划问题的三种常用解法:单纯形法、直接搜索法以及遗传算法,最后在Matlab R2009a环境下进行了仿真.通过结果可以看出,用Matlab求解线性规划问题,可以避免手工的烦琐计算,大大地提高工作效率和结果的准确性.     

基于C#语言的图片插入方法比较

图片是传递与表达信息的重要形式,由于图片数据特殊编码方式,它的存储和显示显得比较复杂。C#功能强大,使用方便,已经成为一种主流的计算机软件编程语言。文章介绍了使用C#向数据库中插入图片的方法,并加以比较。     

浅析广告创意产生的过程

文章将广告创意的产生分为准备、分析、顿悟和评估四个阶段,针对每个阶段的工作重点、工作方法进行阐述,涉及到多种思维方式和创意技巧,旨在说明创意不能仅靠天赋,更应源于科学的方法和步骤。     

高压电气设备支架串联体系地震响应半解析法

通过论述高压电气设备支架串联体系地震响应半解析法的运算过程,说明地震响应半解析法对于电力系统防震工作的帮助。     

烟草制丝线上调节阀流量特性的选择

介绍调节阀的控制原理,分析调节阀流量特性对控制系统的影响,结合烟草设备的工艺特性,提出烟草制丝设备上调节阀流量特性选择的原则。     

COMPILE-TIME ANALYSIS AND OPTIMIZATION OF EXPLICITLY PARALLEL PROGRAMS*

Data flow analysis has been used by compilers in diverse contexts, from optimization to register allocation. Traditional analysis of sequential programs has centered on scalar variables. More recently, several researchers have investigated analysis of array sections for optimizations on modern architectures. This information has been used to distribute data, optimize data movement and vectorize or parallelize programs. As multiprocessors become more common-place. we believe there will be considerable interest in explicitly parallel programming languages. In this paper, we extend traditional analysis to array section analysis for parallel languages which include additional control and synchronization structures.

We show how to compute array section data flow information, i.e., Communication Sets, for a class of parallel programs. To illustrate its use, we show how this information can be applied in compile-time program partitioning. Information about array accesses can also be used to improve estimates of program execution time used to direct runtime thread scheduling.     

Negative effects of sufficiently small initial weights on back-propagation neural networks

In the training of feedforward neural networks,it is usually suggested that the initial weights should be small in magnitude in order to prevent premature saturation.The aim of this paper is to point out the other side of the story:In some cases,the gradient of the error functions is zero not only for infinitely large weights but also for zero weights.Slow convergence in the beginning of the training procedure is often the result of sufficiently small initial weights.Therefore,we suggest that,in these cases,the initial values of the weights should be neither too large,nor too small.For instance,a typical range of choices of the initial weights might be something like(0.4,0.1) ∪(0.1,0.4),rather than(0.1,0.1) as suggested by the usual strategy.Our theory that medium size weights should be used has also been extended to a few commonly used transfer functions and error functions.Numerical experiments are carried out to support our theoretical findings.     

Uniform modeling of parameter dependent nonlinear systems

This paper addresses the problem of approximating parameter dependent nonlinear systems in a unified framework. This modeling has been presented for the first time in the form of parameter dependent piecewise affine systems. In this model, the matrices and vectors defining piecewise affine systems are affine functions of parameters. Modeling of the system is done based on distinct spaces of state and parameter, and the operating regions are partitioned into the sections that we call ’multiplied simplices’. It is proven that this method of partitioning leads to less complexity of the approximated model compared with the few existing methods for modeling of parameter dependent nonlinear systems. It is also proven that the approximation is continuous for continuous functions and can be arbitrarily close to the original one. Next, the approximation error is calculated for a special class of parameter dependent nonlinear systems. For this class of systems, by solving an optimization problem, the operating regions can be partitioned into the minimum number of hyper-rectangles such that the modeling error does not exceed a specified value. This modeling method can be the first step towards analyzing the parameter dependent nonlinear systems with a uniform method.