GPS/电子地图组合定位技术在侦察机器人系统中的应用

介绍了GPS／电子地图组合定位技术在侦察机器人系统中的应用。对GPS接收机进行二次开发，在WINDOWS环境下，基于VB6．0，利用通信控件捕获基准站和移动站的RTCM SC－104格式差分GPS电文。分析比较了几种GPS定位算法的优劣，根据侦察机器人系统的特点，选择逆向伪距差分算法对电文进行处理，并与电子地图相结合进行精确定位。对逆向伪距差分算法的实现做了详细介绍并对实验结果做了简要分析，在电子地图的管理上，提出了将监视区域二次划分的方法，利用BMP位图，对侦察机器人所在的方位进行可视化精确定位。     

非AWGN环境下调制类型自动识别

在非AWGN环境下，针对CW，AM，FM，OOK，PSK，QPSK，16QAM，FSK，MSK，SSB十种混合调制信号，对调制类型特征提取方法和自动识别算法进行了分析、综合、设计和计算机仿真。提出了梯层电平分析方法、频率瞬时信号分析、剔除载波的归一化能量分析、平方后信号的频谱分析、四次方后的信号频谱分析等方法。当SNR=10dB时，计算机仿真结果是正确识别率不低于95％，自动识别的平均处理时间为不超过10s。     

The Effects of Filtered Channel Quality Feedback on Throughput of Proportional Fair Algorithm

1　IntroductionSchedulingalgorithmsarewidelystudiedforwirelesspacketdatasystems,whichgenerallyhavetwobasiccategories,oneisoptimizedforsystemthroughputandfairness[1～ 2 ] ,andtheotherisforthequalityofservice[3～6] .Forsystemswherepack etdataaretimedivisionmultiplexedacrossusersonthedownlink ,orfromBaseStation (BS)tomultipleMobileStations(MS) ,theBSusesschedulingalgo rithmstodecidewhichuseristransmittedto .ItisindicatedinRefs.[7,8]thatschedulingonlyoneus eratatimeisoptimalfromthepointofviewo…     

基于遗传算法的图像边缘信息链表匹配技术

提出了一种基于遗传算法的图像边缘信息链表匹配方法。首先,采用CANNY算子的方法提取图像边缘;然后,将图像边缘信息链表化;最后,基于链表化结果利用遗传算法进行链表匹配。该方法能够减少匹配过程中的计算量,且能实现高效匹配。通过仿真实验,验证了该方法的性能。     

An adaptive non‐conforming finite‐element method for Reissner–Mindlin plates

Adaptive algorithms are important tools for efficient finite‐element mesh design. In this paper, an error controlled adaptive mesh‐refining algorithm is proposed for a non‐conforming low‐order finite‐element method for the Reissner–Mindlin plate model. The algorithm is controlled by a reliable and efficient residual‐based a posteriori error estimate, which is robust with respect to the plate's thickness. Numerical evidence for this and the efficiency of the new algorithm is provided in the sense that non‐optimal convergence rates are optimally improved in our numerical experiments. Copyright © 2003 John Wiley & Sons, Ltd.     

基于混合遗传算法的树状注水管网拓扑优化

以投资最小为目标函数,以井间隶属关系的惟一性、连接注水井数量等限制为约束条件,建立了树状注水管网拓扑优化数学模型.根据模型特点,将优化问题分为分配层和几何层,分别采用遗传算法和非线性优化方法进行求解.并对遗传算法的操作过程进行了改进,调整了适应函数,采用随机多父辈适应函数值加权交叉和多种变异操作,结合了模拟退火算法,并给出了初温的确定方法,改进了选择复制操作,从而形成了混合遗传算法.该算法能够有效地提高收敛速度,避免早熟收敛.利用算例说明了该方法的有效性.     

On the design of multiple key hashing files for concurrent orthogonal range retrieval between two disks

This paper concerns the following problem: given a set of multi-attribute records, a fixed number of buckets and a two-disk system, arrange the records into the buckets and then store the buckets between the disks in such a way that, over all possible orthogonal range queries (ORQs), the disk access concurrency is maximized. We shall adopt the multiple key hashing (MKH) method for arranging records into buckets and use the disk modulo (DM) allocation method for storing buckets onto disks. Since the DM allocation method has been shown to be superior to any other allocation methods for allocating an MKH file onto a two-disk system for answering ORQs, the real issue is knowing how to determine an optimal way for organizing the records into buckets based upon the MKH concept.

A performance formula that can be used to evaluate the average response time, over all possible ORQs, of an MKH file in a two-disk system using the DM allocation method is first presented. Based upon this formula, it is shown that our design problem is related to a notoriously difficult problem, namely the Prime Number Problem. Then a performance lower bound and an efficient algorithm for designing optimal MKH files in certain cases are presented. It is pointed out that in some cases the optimal MKH file for ORQs in a two-disk system using the DM allocation method is identical to the optimal MKH file for ORQs in a single-disk system and the optimal average response time in a two-disk system is slightly greater than one half of that in a single-disk system.     

坐标旋转法的收敛性,误差估计及扩展

本文通过推广正规序列的定义,得到一个不等式,由此证明了统一计算初等函数数值的坐标旋转法的收敛性,作了误差估计,并拓广了所计算的函数范围,成为快速计算所有初等函数的统一算法．     

基于广义最小均方的自适应递归滤波算法

本文提出了一种广义最小均方(GLMS)算法,分析了GLMS算法的性能,并根据GLMS算法,导出一种自适应递归滤波(ARF)算法。在推导中,ARF算法避开了超稳定定理,从而考虑自适应系统的严格正实条件和Popov不等式是不必要的。计算机模拟表明ARF算法具有很高的收敛速度。