有限群的极大子群的正规指数

有限群的结构与其子群性质间的关系问题是群论的一个重要研究方向,通过群的极大子群、正规子群、半正规子群、极大子群的正规指数等去研究群的可解性,超可解性、幂零性等,已有一系列结果.应用极小反例方法,利用有限群极大子群的正规指数,得到了一个有限群是π-可解群的充分条件,2个有限群是π-可解群的充分必要条件.     

正则化方法在非线性分析中的应用

本文用正则化方法给出了麦夸脱方法的一个误差估计式.     

On a class of multiple failure mode systems

The primary objective of this work is to introduce and perform a detailed study of a class of multistate reliability structures in which no ordering in the levels of components' performances is necessary. In particular, the present paper develops the basic theory (exact reliability formulae, reliability bounds, asymptotic results) that will make it feasible to investigate systems whose components are allowed to experience m ≥ 2 kinds of failure (failure modes), and their breakdown is described by different families of cut sets in each mode. For illustration purposes, two classical (binary) systems are extended to analogous multiple failure mode structures, and their reliability performance (bounds and asymptotic behavior) is investigated by numerical experimentation. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 167–185, 2002; DOI 10.1002/nav.10007     

机载脉冲多普勒雷达的自适应旁瓣对消实现方法

简要介绍了自适应旁瓣对消的基本原理。重点研究了自适应旁瓣对消在机载脉冲多普勒雷达中的工程实现方法,该方法打破了自适应旁瓣对消目前只能应用于采用低重脉冲重复周期的脉冲多普勒雷达的限制。通过对自适应旁瓣对消结果的分析,表明该方法完全能够满足现有机载脉冲多普勒雷达抗有源旁瓣干扰的需求。     

反函数的导数定理的一个注记

给出反函数的导数定理的改进形式:若f(x),x∈(a,b)与φ(y),y(A,B)互为反函数,x0∈(a,b),y0=f(x0),φ(y)在点y0处可导且φ′(y)≠0,f(x)在点x0处连续,则f(x)在点x0处可导,且f′(x0)=1/φ′(y0).并说明,f(x)在点x0处连续这一条件不可去掉。     

多元线性模型的广义逆诊断问题

在实际问题中,经常需要考虑多个因变量对多个自变量的相互依赖关系,但在运算过程中经常会碰到奇异矩阵不能求逆的问题.通过推导任意2矩阵的差的广义逆,解决了这一问题,继而得出多元线性模型的参数估计,最后推出数据删除模型异常点的判断依据.     

有限次故障小修模型

针对具有小修的维修策略问题,在提出一定的假设条件后,建立经过长期运行后的单位时间期望损失的模型,研究并分析了有限次故障小修模型,最后通过相应的示例验证了研究结果。     

ISAR成像方位向定标方法研究

提出了一种适合工程应用的ISAR方位向定标方法,通过对相位数据的平滑、分段、拟合,完成了对转速的快捷准确的估算,同时分析了散射点分布对定标精度的影响,结合仿真和试验数据验证了方法的有效性,并根据工程实践的经验,提出了一些提高定标精度的准则。     

采用包络检波去除SISAR直达波干扰的新方法

为了去除直达波干扰,从强的直达波干扰背景中有效提取SISAR侧影成像的目标全息信号,提出了对接收的含有目标全息信号和强直达波的混合信号直接进行包络检波,然后通过对检波后的输出进行时域的正交分解,恢复目标的全息信号的新方法.仿真结果验证了理论分析的正确性.     

Predictability of operational processes over finite horizon

Operational processes are usually studied in terms of stochastic processes. The main information measure used for predictability of stochastic processes is the entropy rate, which is asymptotic conditional entropy, thus not suitable for application over a finite horizon. We use the conditional entropy to study the predictability of stochastic processes over the finite horizon. It is well‐known that the conditional entropies of stationary processes decrease as the processes evolve, implying that, on average, their pasts become more informative about prediction of their future outcomes. Some important operational processes such as martingale, models for maintenance policies, nonhomogeneous Poisson, and mixed Poisson processes are nonstationary. We show that as a nonstationary process evolves, it may provide more information or less information about the future state of the system. We develop results for comparing the predictability of stochastic processes. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011