降低线性调频脉冲压缩信号旁瓣的方法

讨论线性调频脉冲压缩信号距离旁瓣的抑制。研究如何降低小时带积线性调频信号距离旁瓣电平问题,针对该信号频谱矩形特性差,提出了采用频谱修正方法来提高脉冲压缩信号的主副比。该方法具有全数字式处理特点,适宜使用IMS A100器件实现脉冲压缩处理。计算机模拟结果表明,无论是小时带积还是大时带积的线性调频信号,经谱修正后,脉冲压缩信号的主副比均舍得到提高。     

基于Simpson公式改进的FAGM(1,1)模型及其应用研究

本文分析了传统FAGM（1,1）模型建模过程中存在的误差,提出了一种基于Simpson公式改进的FAGM（1,1）模型。首先,基于分数阶累加生成算子和分数阶累减生成算子建立分数阶FAGM（1,1）模型。其次,利用Simpson积分公式对FAGM（1,1）模型的背景值进行改进,建立SFAGM（1,1）模型。进一步,应用遗传算法确定SFAGM（1,1）模型的最优阶数以提高模型的预测精度。最后,以中国人均GDP为例,对比分析GM（1,1）模型、Simpson改进的GM（1,1）模型（SGM（1,1））、FAGM（1,1）模型、SFAGM（1,1）模型的模拟结果,并对"十三五"时期的人均GDP进行预测,其结果表明SFAGM（1,1）模型比GM（1,1）、SGM（1,1）、FAGM（1,1）在人均GDP的预测方面有更高的精度,"十三五"期间人均GDP年平均增长率为10.64%,到2020年达到83146.97元,是2010年人均GDP的2.69倍,以2010年的人均GDP为基准,到2020年将能够实现翻一番的目标。     

Measuring credibility of compensatory preference statements when trade-offs are interval determined

This paper studies how an overall fuzzy preference relation can be constructed in the compensatory context of the simple additive difference model, when imprecision on the trade-offs has to be taken into account. Three credibility indices of preferences are analysed and illustrated by a numerical example. Arguments are presented supporting the use of the third index, for which an interesting transitivity property (which was an open problem) is proved.     

关于全着色Ramsey数

以 X_2(G)记一图 G 之全色数,全着色 Ramsey 数 X_2(m,n)为最小正整数 p,使得每一p 阶图 G 或有X_2(G)≥in加,或其补图■满足 X_2(■)≥n。本文给出 X_2(m,n)的上、下界。     

多元正态分布广义方差区间估计的改进

讨论了多元正态分布广义方差的区间估计问题,给出了在覆盖率及长度上均优于最优仿射同变区间估计的改进估计．     

常系数齐次线性微分方程组与其相应的差分方程组之间的联系

给出了求解常系数线性齐次微分方程组和常系数线性齐次差分方程组的一个方法,指出了这两种方程组之间存在的一个有趣关系．     

初等r-循环矩阵的几个性质

给出了初等ｒ－循环矩阵可逆的充要条件及逆矩阵的表达式;对奇异的初等ｒ－循环矩阵给出了Ａ的一个ｇ－逆Ｇ（满足ＡＧＡ＝Ａ,ＧＡＧ＝Ｇ）及Ｍｏｏｒｅ－ｐｅｎｒｏｓｅ广义逆矩阵的表达式．     

A Population Approach to Analysis of Variance Models

Several authors have contributed to what can now be considered a rather complete theory for analysis of variance in cases with orthogonal factors. By using this theory on an assumed basic reference population, the orthogonality concept gives a natural definition of independence between factors in the population. By looking upon the treated units in designed experiments as a formal sample from a future population about which we want to make inference, a natural parametrization of expectations and variances connected to such experiments arises. This approach seems to throw light upon several controversial questions in the theory of mixed models. Also, it gives a framework for discussing the choice of conditioning in models     

Generalized Leverage and its Applications

The generalized leverage of an estimator is defined in regression models as a measure of the importance of individual observations. We derive a simple but powerful result, developing an explicit expression for leverage in a general M -estimation problem, of which the maximum likelihood problems are special cases. A variety of applications are considered, most notably to the exponential family non-linear models. The relationship between leverage and local influence is also discussed. Numerical examples are given to illustrate our results