Outlier-resistant methods for estimation and model fitting

Least squares is perhaps the most widely used technique for model fitting. In this article, we illustrate the poor performance of least squares when there are spurious values, or outliers, in a sequence of measurements. A brief overview of three well-known classes of robust alternatives to the least-squares mean is presented. For robust regression, a recent proposal called least median squares (LMS) is decribed. LMS regression is compared to least-squares regression in an example involving the estimation of optical fiber geometry. References are provided for software that is available for robust estimation techniques surveyed in this article.     

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.     

线性调频相干激光雷达的信号处理

分析了相干激光雷达线性调频脉冲的产生及其信号处理过程，讨论了该雷达信号体制的处理方法和结果。计算了采用匹配滤波和加权处理结果，对于1MHz／μs的调制速率信号的结果表明，激光相干雷达的测速和测距精度分别可达0.04m／s和0．57m.     

COLLISION DETECTION AMONG MOVING OBJECTSIN MACHINING PROCESS SIMULATION

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西气东输管道工程《管道对接环焊缝全自动超声波检测》标准及与国外先进标准的对比

介绍了西气东输管道工程《管道对接环焊缝全自动超声波检测》标准的技术特点、主要内容,并对本标准与国外先进标准、国外先进企业标准进行了较详细的对比分析。本标准在检测工艺方面与ASTM E1961-98相近。验收部分是从缺欠的位置、缺欠自身高度和长度来加以限制,较为合理,具有科学性,与EN25817-92和ISO5817-92标准相当,比API1104-99标准偏严,与西气东输工程射线检测企业标准也基本相当。     

悬停直升机的雷达探测技术

首先对直升机旋翼的雷达回波进行建模与分析,在此基础上分析了雷达探测悬停直升机的可能性,提出了一种适用于所有直升机类型的多扫描周期积累检测系统方案,讨论了可能影响其检测性能的因素.     

多载波CDMA系统中联合检测译码方法研究

为了提高多载波CDMA(MC-CDMA)系统的抗干扰能力与系统容量,提出了一种将信道参数检测与纠错码译码联合运算进行的方法,得到了一种反馈级联结构.在分析MC-CDMA系统接收性能时,通常假设信道参数能精确估计,但对于时变信道在实现上是困难的;根据本文提出的级联结构,先用导频符号进行信道参数估计,再用导频符号的译码信息作为导频符号进行信道参数的进一步优化,构成一种联合检测译码结构,能有效地降低导频符号数量,并提高了信道参数估计精度.通过仿真,与传统的方法进行了性能比较,联合检测译码方案能获得较大系统增益,是一种优化方案.     

前向反冲分析和非卢瑟福背散射

介绍了弹性散射分析中的另外两种分析方法——前向反冲分析和非卢瑟福背散射分析。前向反冲分析适用于材料中H和He同位素分析。高能质子和He离子背散射分析可提高对重基体中C,N和O等轻元素分析的灵敏度。给出了这两种分析方法的应用实例。     

Voltage sag compensation with minimum energy injection by use of a micro‐SMES

This paper presents a method to compensate voltage sags with minimum energy injection for a series‐connected voltage restorer using a micro‐SMES. A circuit for extracting the fundamental symmetrical components from sag voltages and a minimum energy injection algorithm is described. Simulations of voltage sag compensation have been carried out using PSCAD/EMTDC for various faults. The simulation results confirm the validity of the proposed method and show the possibility of reducing the size of energy storage devices. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(3): 70–80, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10047