Optimal and self‐tuning fusion Kalman filters for discrete‐time stochastic singular systems

Based on the optimal fusion estimation algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion Kalman filter weighted by scalars is presented for discrete‐time stochastic singular systems with multiple sensors and correlated noises. A cross‐covariance matrix of filtering errors between any two sensors is derived. When the noise statistical information is unknown, a distributed identification approach is presented based on correlation functions and the weighted average method. Further, a distributed self‐tuning fusion filter is given, which includes two stage fusions where the first‐stage fusion is used to identify the noise covariance and the second‐stage fusion is used to obtain the fusion state filter. A simulation verifies the effectiveness of the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

一种采用单台微机控制的标签粘贴机

标签粘贴机是一种可自动进行标签打印和粘贴的设备装置,在工业自动化生产中有着广泛的应用.介绍了一种采用单台微机进行控制的全自动标签粘贴机的工作原理及各部分组成,以及使用过程中对其进行设置和调整的方法.该标签粘贴机已实际应用于华飞彩色显示系统有限公司29英寸彩色显像管生产线的屏网组装工序,取得了良好的效果.     

cdma1x无线子系统导频信道功率分配分析

分析了目前联通CDMA网络建设中的主要问题之一——导频功率分配问题。主要介绍了cdma 1x系统的信道类型，以及前向链路信道功率分配原则，并且对导频信道功率与无线网络覆盖和容量之间的关系进行了初步探讨。     

IPv6和基于IPv6的网络设计

对IPv6协议的主要内容进行了简要介绍,并针对IPv6的特点对基于IPv6的网络设计进行了探讨。     

透析3G在中国面临的重重困局(1)--牌照与标准选择

探讨了中国3G牌照何时发放、发放数量、牌照与标准是否捆绑、3G产业链如何搭建、频率如何分配、市场容量和终端等问题，并对此提出了建设性的意见。     

Creating a Student Centered Learning Environment at the University of Denver

A team of faculty members at the University of Denver changed the learning environment in key courses in the Department of Engineering from predominately teacher centered to student centered. Through this funded project new grading methods were implemented, classrooms were renovated and wired with studio layouts to facilitate learning, the Engineering Circuits Laboratory was rewired and instrumented for automated data acquisition and reporting, and two new pedagogical approaches were developed. At the onset of the project, six goals were established related to student learning. The introduction of industry standard hardware and software provided students with unprecedented hands‐on experience and project related activities stimulated faculty innovations in other current and future courses. Assessment results indicate that the new grading system improved the clarity of expectations for students before assignments were given resulting in increased reported motivation for learning in many courses. Even though course GPAs did not always reflect higher achievement on graded work, faculty members firmly believe that deeper understanding was achieved because more complex material was assimilated.     

爆炸焊接——热轧双相不锈钢复合钢板研制

本文主要阐述了通过爆炸焊接和热轧的方法,研制成功可焊性良好的且具有较好强度、韧性与综合性能的双相耐应力腐蚀的不锈复合钢板。还将热轧与热处理的两种试验作了较全面的常规、特殊检验试验,结果完全达到使用要求。