随机共振在微弱信号检测中的数值仿真

对基于非线性双稳系统随机共振的微弱信号检测技术进行数值研究,利用随机共振机制,浸入在噪声中的微弱信号可以得到有效的放大与增强。给出了基于Runge Kutta算法的双稳系统随机共振模型的求解方法,提出了利用随机共振检测微弱非周期信号的一种新思路。数值仿真结果表明,该方法不仅可以检测出强噪声极低频的微弱周期信号,而且可以对非周期信号进行有效的检测。     

高保真语音数字信号获取系统设计与实现

给出了高保真数字信号获取系统的结构,分析了为生成高保真语音数字信号文件应注意的器件选择、电路设计和编程实现方法,总结了高保真数字信号获取系统四个主要环节,提出了相应的设计原则。     

智能水雷主动干扰方法研究

针对传统的扫雷方法在清除智能化水雷引信方面存在的不足,分析了利用主动干扰信号反水雷的思路,通过分析智能引信的工作机理及在干扰背景下对目标信号的检测能力,建立了基于奈曼-皮尔逊准则的主动干扰反水雷模型.针对水雷磁引信,选择电极式电磁扫雷具为干扰源,以中型舰船为保护对象,通过计算三者的相互位置与信噪比的关系,以及水雷检测出...     

具有变时滞的离散型随机BAM神经网络的稳定性

研究一类具有变时滞的离散型随机BAM神经网络。通过构造Lyapunov泛函以及线性矩阵不等式（LMI）,得出了离散系统全局渐近稳定的充分条件。     

基于随机网络的平均维修保障服务时间分析

利用随机网络建模方法在随机工程项目分析中的优越性,建立了不同保障方式下的维修保障过程模型。重点对网络活动中的维修等待时间和维修等待概率进行了分析,利用随机网络的解析算法,确定了维修力量的平均维修保障服务时间分析模型。最后将该方法应用于伴随修理过程,对其平均维修保障服务时间进行了案例分析。     

混沌检测在雷达信号测试中的应用

为解决雷达测试信噪比很小的信号检测问题,分析了噪声特性和多普勒信号特性,论述了混沌检测原理,提出了混沌检测方法,并通过实验对混沌检测的可行性及实用性进行了验证。     

北斗三号新信号体制共视时间比对

为促使北斗系统特别是北斗三号系统尽早加入国际原子时计算,利用中国科学院国家授时中心以及捷克无线电工程和电子学院两个守时实验室接收机产生的北斗三号新信号体制观测数据,开展基于北斗三号新信号体制共视时间比对试验。结果表明,北斗三号信号的多路径噪声影响小于北斗二号信号,且信噪比优于北斗二号信号。对比已有的研究,北斗三号新信号体制(B1C和B2a)共视时间比对的噪声相对于北斗三号卫星播发的北斗二号兼容信号体制(B1I和B3I)有较大的改善,其结果与GPS、Galileo共视比对结果相当,且在零基线共钟比对中,基于北斗三号新信号体制比对钟差的标准偏差相对于北斗二号信号提高了40%以上;利用北斗三号新信号体制共视得到的亚欧两地钟差噪声小于北斗二号信号,且比对钟差的稳定度相对于北斗二号提高了10%以上。该试验也可为北斗三号时间比对纳入国际原子时计算提供相关的研究基础。     

初相未知信号联合检测与估计的序贯实现

在未知参数的充分统计量和再生概率密度函数的基础上,引入了联合检测与估计的序贯算法,给出了算法的实现框图,并将该算法应用于高斯噪声中初相位未知信号的联合检测与估计当中.仿真实验表明,新算法较传统算法有一定的性能改善.     

Approximating nondominated sets in continuous multiobjective optimization problems

Many important problems in Operations Research and Statistics require the computation of nondominated (or Pareto or efficient) sets. This task may be currently undertaken efficiently for discrete sets of alternatives or for continuous sets under special and fairly tight structural conditions. Under more general continuous settings, parametric characterisations of the nondominated set, for example through convex combinations of the objective functions or ε‐constrained problems, or discretizations‐based approaches, pose several problems. In this paper, the lack of a general approach to approximate the nondominated set in continuous multiobjective problems is addressed. Our simulation‐based procedure only requires to sample from the set of alternatives and check whether an alternative dominates another. Stopping rules, efficient sampling schemes, and procedures to check for dominance are proposed. A continuous approximation to the nondominated set is obtained by fitting a surface through the points of a discrete approximation, using a local (robust) regression method. Other actions like clustering and projecting points onto the frontier are required in nonconvex feasible regions and nonconnected Pareto sets. In a sense, our method may be seen as an evolutionary algorithm with a variable population size. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

A generalization of the weighted set covering problem

We study a generalization of the weighted set covering problem where every element needs to be covered multiple times. When no set contains more than two elements, we can solve the problem in polynomial time by solving a corresponding weighted perfect b‐matching problem. In general, we may use a polynomial‐time greedy heuristic similar to the one for the classical weighted set covering problem studied by D.S. Johnson [Approximation algorithms for combinatorial problems, J Comput Syst Sci 9 (1974), 256–278], L. Lovasz [On the ratio of optimal integral and fractional covers, Discrete Math 13 (1975), 383–390], and V. Chvatal [A greedy heuristic for the set‐covering problem, Math Oper Res 4(3) (1979), 233–235] to get an approximate solution for the problem. We find a worst‐case bound for the heuristic similar to that for the classical problem. In addition, we introduce a general type of probability distribution for the population of the problem instances and prove that the greedy heuristic is asymptotically optimal for instances drawn from such a distribution. We also conduct computational studies to compare solutions resulting from running the heuristic and from running the commercial integer programming solver CPLEX on problem instances drawn from a more specific type of distribution. The results clearly exemplify benefits of using the greedy heuristic when problem instances are large. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2005