BFEEDBACK CONTROL OF SINGLE-LINK FLEXIBLE ARMS

ＦＥＥＤＢＡＣＫＣＯＮＴＲＯＬＯＦＳＩＮＧＬＥ－ＬＩＮＫＦＬＥＸＩＢＬＥＡＲＭＳＦＥＮＧＤＥＸＩＮＧ（冯德兴）；ＺＨＡＮＧＷＥＩＴＡＯ（张维韬）（ＩｎｓｔｉｔｕｔｅｏｆＳｙｓｔｅｍｓＳｃｉｅｎｃｅ，ｔｈｅＣｈｉｎｅｓｅＡｃａｄｅｍｙｏｆＳｃｉｅｎｃｅ...     

A SINGULAR SINGULARLY-PERTURBED BOUNDARY VALUE PROBLEM

ＡＳＩＮＧＵＬＡＲＳＩＮＧＵＬＡＲＬＹ－ＰＥＲＴＵＲＢＥＤＢＯＵＮＤＡＲＹＶＡＬＵＥＰＲＯＢＬＥＭ￥ＬｉｎＷｕｚｈｏｎｇ（林武忠）；ＷａｎｇＺｈｉｍｉｎｇ（汪志鸣）（ＥａｓｔＣｈｉｎａＮｏｒｍａｌＵｎｉｖｅｒｓｉｔｙ，上海华东师范大学，邮编：２０００...     

GLOBAL ATTRACTIVITY IN A DISCRETE MODEL OF NICHOLSON'S BLOWFLIES

ＧＬＯＢＡＬＡＴＴＲＡＣＴＩＶＩＴＹＩＮＡＤＩＳＣＲＥＴＥＭＯＤＥＬＯＦ　ＮＩＣＨＯＬＳＯＮ＇Ｓ　ＢＬＯＷＦＬＩＥＳＬｉＪｉｎｇｗｅｎ（李经文）（ＳｈａｏｙａｎｇＴｅａｃｈｅｒｓＣｏｌｌｅｇｅ湖南邵阳师专,邮编;４２２０００）Ａｂｓｔｒａｃｔ：Ｃｏｎｓ...     

SOME RESULTS RELATED TO THE SEPARABLE QUOTIENT PROBLEM

ＳＯＭＥＲＥＳＵＬＴＳＲＥＬＡＴＥＤＴＯＴＨＥＳＥＰＡＲＡＢＬＥＱＵＯＴＩＥＮＴＰＲＯＢＬＥＭ￥（钟怀杰）ＺｈｏｎｇＨｕａｉｊｉｅ（Ｄｅｐｔ．ｏｆＭａｔｈ．，ＦｕｊｉａｎＮｏｒｍａｌＵｎｉｖｅｒｓｉｔｙ，Ｆｕｚｈｏｕ３５０００７，Ｃｈｉｎａ．）Ａｂｓ...     

A CLASS OF SINGULARLY PERTURBED NONLINEAR ROBIN PROBLEMS

ＡＣＬＡＳＳＯＦＳＩＮＧＵＬＡＲＬＹＰＥＲＴＵＲＢＥＤＮＯＮＬＩＮＥＡＲＲＯＢＩＮＰＲＯＢＬＥＭＳＺｈａｏＷｅｉｌｉ（赵为礼）（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ．ＪｉｌｉｎＵｎｉｖｅｒｓｉｔｙ，Ｃｈａｎｇｃｈｕｎ１３００２３，Ｃｈｉｎａ...     

方差分析模型中参数的经验Bayes估计及其优良性问题

本文考虑单向分类的方差分析模型，构造了Ｐ′α的线性Ｂａｙｅｓ估计和经验Ｂａｙｅｓ（ＥＢ）估计，此处αａ×１是效应参数向量，Ｐａ×ｋ是常数矩阵．在较一般的条件下，基于均方误差矩阵准则和ＰｉｔｍａｎＣｌｏｓｅｎｅｓｓ准则，我们分别证明了ＥＢ估计优于最小二乘估计     

THE ALMOST PERIODIC SOLUTION AND BOUNDED SOLUTION OF PERTURBED SYSTEMS

ＴＨＥＡＬＭＯＳＴＰＥＲＩＯＤＩＣＳＯＬＵＴＩＯＮＡＮＤＢＯＵＮＤＥＤＳＯＬＵＴＩＯＮＯＦＰＥＲＴＵＲＢＥＤＳＹＳＴＥＭＳＬｉｎＭｕｒｅｎ（林木仁）（ＦｕｚｈｏｕＵｎｉｖｅｒｓｉｔｙ福州大学，邮编：３５０００２）Ａｂｓｔｒａｃｔ：Ｉｎｔｈｉｓｐａｐｅ...     

THE GLOBAL SMOOTH SOLUTION FOR HIGH-DIMENSIONAL HYPERBOLIC SYSTEMS

ＴＨＥＧＬＯＢＡＬＳＭＯＯＴＨＳＯＬＵＴＩＯＮＦＯＲＨＩＧＨ－ＤＩＭＥＮＳＩＯＮＡＬＨＹＰＥＲＢＯＬＩＣ　ＳＹＳＴＥＭＳＨｕＺｈｉｍｉｎｇ（扈志明）ＺｈａｎｇＴｏｎｇ（张同）（ＩｎｓｔｉｔｕｔｅｏｆＭａｔｈｅｍａｔｉｃｓ，Ｃｈｉｎ．Ａｃａｄ．ｏｆＳｅ...     

TIME OPTIMAL IMPLUSE CONTROL PROBLEMS

ＴＩＭＥ　ＯＰＴＩＭＡＬ　ＩＭＰＬＵＳＥ　ＣＯＮＴＲＯＬ　ＰＲＯＢＬＥＭＳＴＩＭＥＯＰＴＩＭＡＬＩＭＰＬＵＳＥＣＯＮＴＲＯＬＰＲＯＢＬＥＭＳ￥ＸｕＺｏｎｇｙｕｎ（ＦｕｄａｎＵｎｉｖｅｒｓｉｔｙ，）Ａｂｓｔｒａｃｔ：Ｉｎｔｈｉｓｐａｐｅｒ，ａｃｌａｓｓ...     

ON THE OPTIMALITY IN GENERAL SENSE FOR ODD-BLOCK SEARCH

ＯＮＴＨＥＯＰＴＩＭＡＬＩＴＹＩＮＧＥＮＥＲＡＬＳＥＮＳＥＦＯＲＯＤＤ－ＢＬＯＣＫＳＥＡＲＣＨ￥ＣＨＥＮＭＵＦＡ（陈木法）（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ，ＢｅｉｊｉｎｇＮｏｒｍａｌＵｎｉｖｅｒｓｚｔｙ，Ｂｅｉｊｉｎｇ１００８７５，Ｃ...     

Bayes估计与最小二乘估计的一个新的相对效率

考虑在错误的先验假定下线性模型回归系数的Bayes估计,将其与最小二乘估计进行比较,提出了Bayes估计与LSE的一种新的相对效率e5,给出了e5的基本性质,同时导出了它的上下界．     

错误先验假定下Bayes线性无偏估计的稳健性

本文基于错误的先验假定获得了一般线性模型下可估函数的Bayes线性无偏估计(BLUE), 证明了在均方误差矩阵(MSEM)准则和后验Pitman Closeness (PPC)准则下BLUE相对于最小二乘估计(LSE)的优良性, 并导出了它们的相对效率的界, 从而获得BLUE的稳健性.     

The Superiorities of Simultaneous Empirical Bayes Estimation for the Regression Coefficients and Error-Variance in Linear Model

When the hyperparameters of prior distribution are partly known in linear model, the simultaneous parametric empirical Bayes estimators (PEBE) of the regression coefficients and error variance are constructed. The superiority of PEBE over the least squares estimator (LSE) of regression coefficients is investigated in terms of the the mean square error matrix (MSEM) criterion, and the superiority of PEBE over LSE of the error variance is discussed under the the mean square error (MSE) criterion. Finally, when all hyperparameters are unknown, the PEBE of regression coefficients and error variance are reconstructed and the superiority of them over LSE under the MSE criterion are studied by simulation methods.     

Superiority of empirical Bayes estimation of error variance in linear model

In this paper, the Bayes estimator of the error variance is derived in a linear regression model, and the parametric empirical Bayes estimator (PEBE) is constructed. The superiority of the PEBE over the least squares estimator (LSE) is investigated under the mean square error (MSE) criterion. Finally, some simulation results for the PEBE are obtained.     

The superiorities of bayes linear unbiased estimator in multivariate linear models

In this article,the Bayes linear unbiased estimator (BALUE) of parameters is derived for the multivariate linear models.The superiorities of the BALUE over the least square estimator (LSE) is studied in terms of the mean square error matrix (MSEM) criterion and Bayesian Pitman closeness (PC) criterion.     

Bayes估计的进一步研究及其Pitman最优性

对线性模型参数,讨论了Bayes估计的Pitman最优性,将已有结果进行了改进,去掉了附加条件,证明了在Pitman准则下,Bayes估计一致优于最小二乘估计(LSE),在此基础上,提出了一种基于先验信息的方差分量估计,通过和基于LSE的方差分量估计作比较,证明了新估计是无偏估计且有更小的均方误差．最后,证明了在Pitman准则下生长曲线模型参数的Bayes估计优于最佳线性无偏估计．     

回归系数的广义岭型主相关估计及其优良性

In this paper, we propose a new biased estimator of the regression parameters, the generalized ridge and principal correlation estimator. We present its some properties and prove that it is superior to LSE （least squares estimator）, principal correlation estimator, ridge and principal correlation estimator under MSE （mean squares error） and PMC （Pitman closeness） criterion, respectively.     

线性模型参数向量的近似贝叶斯估计

用线性贝叶斯方法去同时估计线性模型中回归系数和误差方差,并在不知道先验分布具体形式的情况下,得到了线性贝叶斯估计的表达式.在均方误差矩阵准则下,证明了其优于最小二乘估计和极大似然估计.与利用MCMC算法得到的贝叶斯估计相比,线性贝叶斯估计具有显式表达式并且更方便使用.对于几种不同的先验分布,数值模拟结果表明线性贝叶斯估...     

最小一乘估计快速算法

最小二乘估计容易受奇异点的影响, 最小一乘估计是稳健估计, 可以很好地克服这个缺陷, 但计算困难. 基于非退化模型假设下的稳定极点理论, 本文找到了快速准确求解最小一乘估计的迭代算法,并给出算法的计算过程及与线性规划求解的比较, 较好地解决了最小一乘估计计算难的问题, 使其成为有效的参数估计方法.     

线性模型中回归系数和误差方差的同时Bayes估计的优良性

在线性模型中回归系数与误差方差具有正态-逆Gamma先验时,导出了回归系数与误差方差的同时Bayes估计.在均方误差矩阵准则和Bayes Pitman closeness准则下,研究了回归系数的Bayes估计相对于最小二乘(LS)估计的优良性,还讨论了误差方差的Bayes估计在均方误差准则下相对于LS估计的优良性.