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.     

基于信息的智能控制理论研究

本文介绍的基于信息的智能控制理论的发展过程，主要分为智能控制的信息指标和智能控制的信息结构分析两部分，文中在最后对这套理论可能的发展方向进行了探讨。     

高速网络协议：问题与答案

作者在本文中指出了吉比特网络的目标及其所带来的问题，采用了提出问题并回答问题（或说明可能答案）的方法来阐明。     

An algorithm for architecture partitioning in high-speed networks with bursty traffic

This paper analyzes the performance of a switching architecture. The performance measures include the elapsed time of packet transfer and the waiting time to begin transfer. The architecture is partitioned depending on the type of network used and the expected traffic in the network. Every partition has a switch with a buffer that can absorb surges of bursty traffic within the network partition. The buffer size depends on the type of the network and incoming traffic. The partition size depends on the network bandwidth, network traffic, packet size and buffer size. Examples of different networks are used to show the applications of the model. The results show that the elapsed time of packet switch transfer depends exponentially on the number of partitions in the network.     

易护理的Tencel纺织品

对于今天的织物，易护理性是一项基本要求。然而，理想的易护理效果不可能仅通过Tencel纤维本身的性能来获得，合适的织物组织结构、恰当的前处理，以及最佳的高级整理加工可以提高Tencel织物的易护理性能，并超过其他纤维素纤维。关于织物组织结构的影响已经在其他杂志上有过讨论。本文将说明如何采用不同的前处理、后整理加工，获得高档最终产品的方法。     

考虑变质量湍流影响的水平井流入动态分析

在水平井生产过程中,井筒内管流与地层渗流互相制约、互相影响、互为边界条件,从而构成了一个完整的水动力学体系。根据水平井生产时井筒内管流与油藏的相互作用关系,建立了水平井筒存在压力梯度的变质量湍流与地层渗流的耦合计算新方法。关于井筒内流的计算;应用了经典的k_εM湍流模型,关于地层的渗流计算,采用了有限元法。通过耦合模拟获得了井筒内湍流场流速分布及总压能损耗的规律,根据耦合模拟计算结果绘出了较为准确的水平井流入动态曲线。该计算方法为描述水平井流入动态、评价水平井产能、确定合理生产制度提供了可靠的手段.     

孤岛油田西区聚合物驱开发研究

孤岛油田西区注聚区1997年3月投入注聚后，高渗层得到有效封堵，吸水剖面得到明显改善。注聚期间，通过实施注聚区外围水井降水或停注、油井放大生产压差和调整注聚井注入速度等开发措施，扩大了聚合物波及体积，聚合物驱取得了明显效果。     

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。