关于国有中型企业退出国有序列的几个认识问题

理论界一部分人对国有中型企业退出国有经济序列深感忧虑.其实,相当数量的国有中型企业退出国有序列,没有违反而是适应了生产力的发展要求,没有削弱而是增强了社会主义市场经济条件下国有经济的主导作用,没有损害而是有利于公有制经济的巩固和发展.     

一种新的波达估计方法

分析了目前常用的波达角估计算法,研究了等距线阵和圆阵的特点,指出其存在关于横轴镜像对称信号源的空间模糊性,利用等距T型阵克服了这一困难。提出了一种新的基于训练序列波角达估计新算法,新算法基于如下假设:各个信号源的训练序列互相正交,并且各个信号源都是幅度为1的恒模信号。该文给出了新算法的数学推导过程,得到一个简单的波达角估计公式。应用Matlab对新算法进行了仿真,仿真结果表明新算法能够快速、精确地估计波达方向。     

养老保险融资机制的法律反思

中国养老保险融资机制存在三重侧面,即法规文件上的"统账结合制"、实质规范上的"完全基金制"和现实运行上的"现收现付制",表现出中国养老保险融资机制规范与事实之间存在巨大鸿沟,极大阻碍了制度的有效运行。养老保险制度应促进劳资协作和社会团结的制度目的,决定了"统账结合制"区分个人账户与统筹账户,并由用人单位承担绝大部分养老保险费率的做法,很值得商榷。尽管现收现付制在面对人口老龄化时会相对较快地表征出支付不能,但出于互助共同体的本质要求,养老保险融资机制也应恪守"保险原则",保证资金的专款专用,以使养老保险基金能在最大程度上远离资本市场的不确定性,确保养老保险收支的稳定性,减轻政府的政治和经济风险,避免国家被资本垄断所绑架,故而现收现付制相比于基金制更为可取。在充分借鉴国外有益经验,并结合中国具体国情之后,未来中国养老保险融资机制应考虑通过废除"个人账户",贯彻养老保险收支当期平衡,以实现单一账户制下的现收现付。     

基于离差最大化的组合评价方法研究

本文提出了一种基于离差最大化的组合评价方法,该方法首先利用多个单一评价方法对决策对象评价值之间的总离差达到最大的思想将各单一的评价值组合起来,得到各决策方案的组合评价结果并对其进行排序;其次,设计并采用组合误差平方和对组合评价的效果进行度量。最后结合实例,将本文提出的组合评价方法与平均值组合法、模糊Borda组合法进行对比分析,结果表明该组合评价方法的组合误差更小,有效性更强。     

《文选》再选本说献疑

《文选》再选本说影响深远。但从《文选》所录作品之同篇异名的复杂现象来看,难以成为《文选》乃据前贤总集再选编而非作者别集选录的内证。《文选》所录诗文的部分作品存在着同篇异名、多名,甚至“因类改名”现象,亦有采自时文名篇、经史之文等的可能,由此可推断出《文选》再选本说并不坚确。较为妥当的说法当是初选与再选的合选本,其作品编录来源多样,既有总集、别集及单篇者,又含有史、经二部之作。     

灰色组合预测模型及其应用

针对传统回归模型需要的数据量大且建模复杂等缺陷,提出了一种基于灰色关联度和GM(1,1)的灰色组合预测模型;从灰色关联度的视角寻找数据之间的依赖关系,运用GM(1,1)模型预测数据关系的未来发展趋势,进而建立因变量的预测模型;模型体现了回归分析基于事物因果关系的建模思想,同时又具有灰色理论小样本建模的特点;应用该模型对我国2007和2008年度的GDP进行预测,预测结果表明了该模型的有效性及实用性。     

Generalized linear models and transformations for unreplicated factorial experiments in the presence of dispersion effects

For the analysis of replicated designs, many different methods have been suggested. These allow for the estimation of functional dependencies between mean and variance as well as possible dispersion effects within the same model framework. However, in the situation of unreplicated designs, most methods known so far rely on the assumption of constant variances, or a functional relationship between mean and variance as the only source of heteroscedasticity. In this paper, we propose two methods for dealing with unreplicated data, when dispersion effects might also be of importance. One of these is an extension of the Box–Cox-method [Box, G.E.P., Cox, D.R., 1964. An analysis of transformations. Journal of the Royal Statistical Society B 26, 211–252], the other is based on double generalized linear models. Both these methods turn out to yield approximately equivalent results in the case of comparable assumptions, whereas the double generalized linear model is the more general one and allows further extensions. If this class of models is assumed, consistency, asymptotic efficiency and normality of the resulting estimates are shown.     

Locating and detecting arrays for interaction faults

The identification of interaction faults in component-based systems has focused on indicating the presence of faults, rather than their location and magnitude. While this is a valuable step in screening a system for interaction faults prior to its release, it provides little information to assist in the correction of such faults. Consequently tests to reveal the location of interaction faults are of interest. The problem of nonadaptive location of interaction faults is formalized under the hypothesis that the system contains (at most) some number d of faults, each involving (at most) some number t of interacting factors. Restrictions on the number and size of the putative faults lead to numerous variants of the basic problem. The relationships between this class of problems and interaction testing using covering arrays to indicate the presence of faults, designed experiments to measure and model faults, and combinatorial group testing to locate faults in a more general testing scenario, are all examined. While each has some definite similarities with the fault location problems for component-based systems, each has some striking differences as well. In this paper, we formulate the combinatorial problems for locating and detecting arrays to undertake interaction fault location. Necessary conditions for existence are established, and using a close connection to covering arrays, asymptotic bounds on the size of minimal locating and detecting arrays are established.     

基于自适应旁瓣对消的测角研究

自适应波束形成(ADBF)和自适应旁瓣对消算法都能够很好地抑制旁瓣干扰,但是由于干扰协方差矩阵的影响,ADBF在抑制干扰同时给和、差单脉冲测角带来误差.文中针对自适应旁瓣对消算法,系统研究了其在和、差单脉冲测角中的应用,着重分析了辅助天线中的目标信号对测角性能的影响.理论分析和仿真结果表明,辅助天线中的目标信号对测角的影响主要存在于辅助天线的增益大于差波束增益的角域,而在其他角域,影响很小.     

基于CORDIC的无开方GIVENS旋转处理方法

自适应阵列处理能提高通信雷达等电子系统的抗干扰能力，因而获得了广泛的应用。许多重要的高速实时自适应阵列处理算法均需要采用一系列Ｇｉｖｅｎｓ旋转处理将输入数据矩阵变成三角阵。标准的Ｇｉｖｅｎｓ旋转包含开方运算，该运算是限制有关算法速度的一个重要因素。文中提出一种基于坐标旋转计算机技术的无开方Ｇｉｖｅｎｓ旋转处理方法，可以显著提高自适应算法的处理速度，并给出了这一方法的推导、Ｇｉｖｅｎｓ处理节点运算式和采用，这种方法的ＱＲ分解自适应阵并行处理算法的计算机模拟结果。