行业统计报表处理系统SRAFT的设计与实现

分析了行业统计工作中报表制度编制和报表数据处理的特点，给出了一个计算及审核公式的描述方法，设计并实现了一个由报表框架设计器、计算及审核公式管理器、数据汇总项目管理器、填报单位管理器、报表数据处理器等5个部分组成的统计报表处理系统SRAFT。     

EDPF-NT分散控制系统在215MW机组上的应用情况分析

介绍中国电科院EDPF-NT分散控制系统在漳泽发电厂苏制215MW机组热控改造中的应用情况,运行实践说明该系统组态灵活、功能丰富、人机界面友好、控制水平高、运行可靠、经济效益显著,可满足大型火电机组监控要求.     

顺序统计的一种算法

本文给出一种在顺序统计中找第ｋ大元素的有效方法。它利用划分元素确定第ｋ大元素的位置。该算法的平均特性为Ｏ（ｎ），其中ｎ是输入元素的个数。     

A Spurious Equilibria-free Learning Algorithm for the Blind Separation of Non-zoer Skewness Signals

We present a new learning algorithm for the blind separation of independent source signals having non-zero skewness (the 3rd-order cumulant) (the source signals have non-symmetric probability distribution.), from their linear mixtures. It is shown that for a class of source signals whose probability distribution functions is not symmetric, a simple adaptive learning algorithm using quadratic function (f(x)=x²) is very efficient for blind source separation task. It is proved that all stable equilibria of the proposed learning algorithm are desirable solutions. Extensive computer simulation experiments confirmed the validity of the proposed algorithm.     

Robust Estimation of Rotation Angles from Image Sequences Using the Annealing M-Estimator

A robust method is presented for computing rotation angles of image sequences from a set of corresponding points containing outliers. Assuming known rotation axis, a least-squares (LS) solution are derived to compute the rotation angle from a clean data set of point correspondences. Since clean data is not guaranteed, we introduce a robust solution, based on the M-estimator, to deal with outliers. Then we present an enhanced robust algorithm, called the annealing M-estimator (AM-estimator), for reliable robust estimation. The AM-estimator has several attractive advantages over the traditional M-estimator: By definition, the AM-estimator involves neither scale estimator nor free parameters and hence avoids instabilities therein. Algorithmically, it uses a deterministic annealing technique to approximate the global solution regardless of the initialization. Experimental results are presented to compare the performance of the LS, M- and AM-estimators for the angle estimation. Experiments show that in the presence of outliers, the M-estimator outperforms the LS estimator and the AM-estimator outperforms the M-estimator.     

数理统计在电池新品开发和科研中的应用

介绍了数理统计学中的单因素方差分析、双因素方差分析、随机化分组在电池新品开发和科研中的应用,采用Excel软件中的数据分析工具,结合实例,使复杂的统计计算可以在数分钟内完成,人们可以很方便地应用方差分析和随机化分组等方法设计试验方案和处理试验中获得的数据,达到指导电池开发和研究的目的。     

Variation in Reliability and Quality

Engineering products are characterized by many parameters, such as weight, dimensions, electrical and mechanical parameters, power consumption, flow rates, and son on. Products are used in a range of conditions, such as temperature, humidity, vibration, power supply values, and so on. In practical situations of manufacture, test and operation these are all subject to variation. How these variations can affect manufacturing, operation and reliability can, in theory, be assessed using statistical methods. This tutorial explains the nature of variation as it affects engineering products, and describes how variation should be dealt with in design, manufacture and test. Copyright © 2004 John Wiley & Sons, Ltd.     

多元统计分析在企业财务危机预警中的应用

主要针对我国家电业上市公司,利用其公开披露的年报财务信息和数据,运用聚类分析法、判别分析法和主成份分析法等多元统计分析方法,并借助于SPSS统计分析软件,建立多变量预测模型进行企业财务危机预警的实证分析.利用财务危机预警体系,企业可以预先发现将有可能出现的财务危机.分析研究方法可供国内的上市公司和非上市公司进行财务危机预警分析的参考.     

数控轴承磨床故障模式及其原因

通过对 2 5台国产数控 (ComputerizedNumericalControl,CNC)轴承磨床的故障数据两年多的跟踪记录 ,获得了较为丰富准确的CNC轴承磨床可靠性数据 ,并基于大型关系型数据库技术建立了CNC轴承磨床可靠性数据库 ,对国产数控轴承磨床的故障部位、故障模式及故障原因进行了详细的统计分析 ,指出了数控轴承磨床的薄弱环节及其潜在弱点 ,为CNC轴承磨床进行可靠性分析和设计提供了依据     

A new second-order method for blind signal separation from dynamic mixtures

This paper presents a new approach to separate colored stationary signals mixed by convolutive channels. A cost function is proposed by employing linear constraint to the demixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.