一类具变号非线性项和p-Laplacian算子的仇点·边值问题的多个正解

研究一类具Laplacian算子的m点边值问题（Ф（u＇））＇＋q（t）f（t,u）=0,0〈t〈1,u（0）=^m-2∑i=1aiu（ζi）,u＇（1）=βu＇（0）.利用锥上的不动点指数定理,对上述具有变号的非线性项的边值问题进行研究,得到多个正解存在的充分条件．     

关于正定厄米特矩阵的一个定理

本文证明了关于正定厄米特矩阵行列式的一个不等式 :若Ai,Bi,…… ,Ci(i =1,2 ,…… ,k)都是n阶正定厄米特矩阵 ,α ,β ,…… ,γ都是正实数 ,并且α +β +…… +γ =p≥ 1则 ki=1|Ai|α·|Bi|β…… |Ci|γ< ki=1 Ai α· ki=1 Bi β…… ki=1 Ci γ     

一类m-点边值问题的正解

研究一类二阶m-点边值问题u″ f(t,u,u)′=0,00,i=1,…,m-2,ζi满足0=ζ0<ζ1<ζ2<…<ζm-2<ζm-1=1和i∑=1aiζi<1。应用推广的Krasnosel-skii′s不动点定理,给出了上述边值问题至少存在一个正解的充分条件。     

非常余维数的未定向协边子群

本文在如下情况:(1)取定P(1≤P≤8),设K_i=8l_i P(i=1,…,l),k_2>9/4(k_1-1)>O;(2)取定整数q(l≤q≤4)式,设k_1=4t_1 q(i=1,…,l),k_2>5/2(k_1-1)>0满足时,决定了一些非常非常余维数的未定向协边子群J_n~(k_1…k_l).     

一类广义L-统计量的极限分布

假定(X1,Y1),(X2,Y2),…,(Xn,Yn)是取自二维随机向量(X,Y)的独立同分布样本.记X(1)≤X(2)≤…≤X(n)是X1,X2,…,Xn产生的次序统计量,Y[1],Y[2],…,Y[n]是诱导的次序统计量.讨论广义L-统计量Tn=n-1 n∑i=1 J(i/n+1)Y[i]的极限分布,式中J(x)是由实际问题的需要而选取的权函数.在较弱的条件下,证明了Tn的渐近正态性,同时给出了Tn的期望和方差的渐近公式.     

四参数寿命分布S(α,β,λ,μ)

本文提出一个具有密度函数 (α>0,β≠0,λ>0,μ≥0)的四参数寿命分布S(α,β,λ,μ),然后证明了它的一些基本性质,据形状参数对(α,β)的不同取值,找出了失效率λ(t)关于时间t的五种变化规律:不变;递减;递增;先增后减;先减后增,并显示出不变失效率是其余四种失效率当(α,β)→(1,1)时的极限。     

q∝△(T~(-1))传热时三热源热泵的最优性能普遍关系

本文导出工质与三个热源间的传热系数分别为。α、β和γ,传热规律为q~∝△(T~(-1))时,内可逆三热源热泵的最佳供热系数ψ与供热率Π间的关系:ψ<1时,Π=K_1ψ[T_p(T_H-T_ο)-T_H(T_p-Tο)ψ]/[T_HT_pT_ο(1-△_1ψ)~2];ψ>1时,Π=K_2ψ[T_p(T_H-T_ο)-T_H(T_P-T_ο)ψ]/[T_HT_pT_ο(△_2-ψ)~2];式中,K_1=αγ/(α~(1/2)+γ~(1/2))~2,K_2=βγ/(β~(1/2)+γ~(1/2))~2,△_1=(α/β)~(1/2)(β~(1/2)-r~(1/2)/(α~(1/2)+γ~(1/2)),△_2=(β/α)~(1/2)(α~(1/2)-γ~(1/2))/(β~(1/2)+γ~(1/2))。由此可得许多有用的关系。     

火控系统数据处理中的误差分离自动寻优方案

在火控系统的精度试验中,由机上测量设备(同步相机、磁带机、示波器等)和地面精测设备(电影经纬仪、雷达等),以一定的采样率实时测得系统各参数输出实际值 x_i 和真值 x_i′,可得到一次差y_i~*=x_i-x_i′(i=1,2……n),如图1所示。对于这些误差数据进行数学统计处理,可求得系统误差(?)和随机误差σy~2。由此来衡量火控系统是否满足战术技术指标的要求。     

多目标跟踪的数据互联——使用分层博尔兹曼机求解

数据互联是确定多目标跟踪算法中的量测源和分配概率β_i~t问题,其中β_i~t是表示第i个量测来自第t个目标这一事件的概率。本文介绍使用一个分层博尔兹曼机求解数据互联问题的新并行计算方法。研究证明,如果能得到充分多的二元神经元层数,就可以用任意小的误差计算互联概率。特别是,证明了概率β_i~j等于分层的两维网络中神经元v(i,j)激发的相对频率。文中还介绍一些简单的跟踪例子,这些例子将对用于精确的数据互联解的博尔兹曼算法的性能与使用Hopfield神经网络的另一种并行算法的性能进行比较。     

基于语音分段的自适应时长调整算法

文中提出了一种自适应的语音时长调整算法,首先对语音分段,提取出稳定的语音段使之与音素或者音节基本对应,然后根据总调整因子β和各段语音长度分配每一个语音段的局部调整因子iβ,最后采用波形相似叠加(W SOLA)算法完成对语音的时长调整。仿真结果表明:文中算法实用有效,可以合成可懂度和自然度更高的语音。     

线性回归模型系数Stein估计的改进研究

针对线性回归模型病态的根本原因,提出了一类新的估计———c-k型估计,将岭估计与Stein估计统一到一个估计类;研究了这一估计类,证明利用岭回归技术可以改进著名的Stein估计(在均方误差意义下);同时研究了相应参数的最优值,分别给出了它的一个上界及下界,为病态线性回归模型系数的有偏估计提供了改进的技术途径.     

An analysis of constrained robust regression estimators

Multicollinearity and nonnormal errors are problems often encountered in the application of linear regression. Estimators are proposed for dealing with the simultaneous occurrence of both multicollinearity and nonnormality. These estimators are developed by combining biased estimation techniques with certain robust criteria. An iteratively reweighted least-squares procedure is used to compute the estimates. The performance of the combined estimators is studied empirically through Monte Carlo experiments structured according to factorial designs. With respect to a mean-squared-error criterion, the combined estimators are superior to ordinary least-squares, pure biased estimators, and pure robust estimators when multicollinearity and nonnormality are present. The loss in efficiency for the combined estimators relative to least squares is small when these problems do not occur. Some guidelines for the use of these combined estimators are given.     

Optimal sample size allocation for tests with multiple levels of stress with extreme value regression

In this article, we discuss the optimal allocation problem in a multiple stress levels life‐testing experiment when an extreme value regression model is used for statistical analysis. We derive the maximum likelihood estimators, the Fisher information, and the asymptotic variance–covariance matrix of the maximum likelihood estimators. Three optimality criteria are defined and the optimal allocation of units for two‐ and k‐stress level situations are determined. We demonstrate the efficiency of the optimal allocation of units in a multiple stress levels life‐testing experiment by using real experimental situations discussed earlier by McCool and Nelson and Meeker. Monte Carlo simulations are used to show that the optimality results hold for small sample sizes as well. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

局部线性估计在半参数条件矩中的应用

半参数方法在计量经济领域有着广泛的应用，但由于其既有参数变量，又有未知函数，因此采用条件矩限制和Sieve方法来得到其参数估计是一个比较好的方法。作为一种非参数回归方法，局部线性估计具有优良的统计特性，因此本文用它来得到条件矩的一个非参数估计，并在此基础上证明了估计参数的一致性和收敛速率。     

Combining standardized time series area and Cramér–von Mises variance estimators

We propose three related estimators for the variance parameter arising from a steady‐state simulation process. All are based on combinations of standardized‐time‐series area and Cramér–von Mises (CvM) estimators. The first is a straightforward linear combination of the area and CvM estimators; the second resembles a Durbin–Watson statistic; and the third is related to a jackknifed version of the first. The main derivations yield analytical expressions for the bias and variance of the new estimators. These results show that the new estimators often perform better than the pure area, pure CvM, and benchmark nonoverlapping and overlapping batch means estimators, especially in terms of variance and mean squared error. We also give exact and Monte Carlo examples illustrating our findings.© 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

A mathematical programming approach for improving the robustness of least sum of absolute deviations regression

This paper discusses a novel application of mathematical programming techniques to a regression problem. While least squares regression techniques have been used for a long time, it is known that their robustness properties are not desirable. Specifically, the estimators are known to be too sensitive to data contamination. In this paper we examine regressions based on Least‐sum of Absolute Deviations (LAD) and show that the robustness of the estimator can be improved significantly through a judicious choice of weights. The problem of finding optimum weights is formulated as a nonlinear mixed integer program, which is too difficult to solve exactly in general. We demonstrate that our problem is equivalent to a mathematical program with a single functional constraint resembling the knapsack problem and then solve it for a special case. We then generalize this solution to general regression designs. Furthermore, we provide an efficient algorithm to solve the general nonlinear, mixed integer programming problem when the number of predictors is small. We show the efficacy of the weighted LAD estimator using numerical examples. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Pickands型推广估计量的渐近正态性

极值指数在许多实际领域广泛应用:如组合投资、风险值的计算、预报地震等, 估计极值指数γ以及它的性质的研究近年来成为极值统计理论的基本问题。主要研究极值指数γ的一个估计量:Pickands型推广估计量的渐近正态性质。首先研究由Pickands型推广估计量构成的一随机过程,得到了该过程的渐近分布;然后利用研究结果证明了Pickands 型推广估计量的渐近正态性,得到其渐近方差;最后对提出的Pickands型推广估计的平滑估计量进行了相应研究。     

A performance comparison of empirical Bayes and Bayes estimators of the Weibull and gamma scale parameters

A mean-squared error comparison of smooth empirical Bayes and Bayes estimators for the Weibull and gamma scale parameters is studied based on a computer simulation. The smooth empirical Bayes estimators are determined as functions of up to 15 past estimates of the parameter of interest. Results indicate that at best the mean-squared errors of the empirical Bayes estimators are about 20–40% larger than those of the corresponding squared-error optimal Bayes estimators.     

病态线性回归模型系数的0─c型岭估计

针对病态线性模型病态的实质,提出回归系数的０－ｃ型岭估计。首先研究它的均方误差的最优化问题,给出了参数的最优值或最优值的一个上界和下界,证明可以选择参数,使它在均方误差的意义下优于ＬＳ估计。其次,研究它的偏差,证明存在０－ｃ型岭估计优于ＬＳ估计,且比岭估计β（ｋ）具有较小偏差。最后证明它的可容许性,并讨论在实用中它的岭参数选择方法的优点。     

Signal‐to‐interference‐plus‐noise ratio estimation for wireless communication systems: Methods and analysis

The Signal‐to‐Interference‐plus‐Noise Ratio (SINR) is an important metric of wireless communication link quality. SINR estimates have several important applications. These include optimizing the transmit power level for a target quality of service, assisting with handoff decisions and dynamically adapting the data rate for wireless Internet applications. Accurate SINR estimation provides for both a more efficient system and a higher user‐perceived quality of service. In this paper, we develop new SINR estimators and compare their mean squared error (MSE) performance. We show that our new estimators dominate estimators that have previously appeared in the literature with respect to MSE. The sequence of transmitted bits in wireless communication systems consists of both pilot bits (which are known both to the transmitter and receiver) and user bits (which are known only by the transmitter). The SINR estimators we consider alternatively depend exclusively on pilot bits, exclusively on user bits, or simultaneously use both pilot and user bits. In addition, we consider estimators that utilize smoothing and feedback mechanisms. Smoothed estimators are motivated by the fact that the interference component of the SINR changes relatively slowly with time, typically with the addition or departure of a user to the system. Feedback estimators are motivated by the fact that receivers typically decode bits correctly with a very high probability, and therefore user bits can be thought of as quasipilot bits. For each estimator discussed, we derive an exact or approximate formula for its MSE. Satterthwaite approximations, noncentral F distributions (singly and doubly) and distribution theory of quadratic forms are the key statistical tools used in developing the MSE formulas. In the case of approximate MSE formulas, we validate their accuracy using simulation techniques. The approximate MSE formulas, of interest in their own right for comparing the quality of the estimators, are also used for optimally combining estimators. In particular, we derive optimal weights for linearly combining an estimator based on pilot bits with an estimator based on user bits. The optimal weights depend on the MSE of the two estimators being combined, and thus the accurate approximate MSE formulas can conveniently be used. The optimal weights also depend on the unknown SINR, and therefore need to be estimated in order to construct a useable combined estimator. The impact on the MSE of the combined estimator due to estimating the weights is examined. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004