东晋南朝土断“阶段性”特征刍议

南朝土断着重于对侨置政区的整顿，其所针对的社会群体也发生明显变化，这两方面内容构成了与东晋土断不同的“阶段性”特征。     

变系数时滞神经网络的周期解与稳定性

针对具有实际应用价值的时滞周期时变系数的Hopfield神经网络系统,利用了Lyapunov函数法并结合不等式分析技巧,证明了系统的解是有界的,得到了系统周期解的存在准则及平凡解指数稳定的充分条件。     

Periodic Solutions of Linear Neutral Differential Equations

研究了具有无穷时滞的线性中立型方程与高阶中立型方程的周期解问题。利用Ｆｏｕｒｉｅｒ指数级数理论，获得了线性中立型方程存在周期解的充分必要条件。文中用例子说明了结果的实用性。     

Boussinesq方程组的行波解研究

运用动力系统定性理论,提出一种分析非线性系统解的方法.并以Boussinesq方程为例,避免了求解的繁琐过程,得到解的几何特性.分析结果表明,在一定参数条件下,Boussinesq方程的相图中存在孤波、扭结波以及周期波.     

关于一类差分方程动力性质的注记

本文对［２］讨论过的一类差分方程进一步讨论其动力性质。     

角向周期结构静电电子回旋脉塞

提出了一种角向周期结构静电电子回旋脉塞的方法。用流体线性理论导出了这种脉塞的色散方程和增长率公式,并进行了相应的分析与计算。此结构能较好地克服正常同轴波导静电电子回旋脉塞工作频率难以提高的困难,并且该结构中的多种角向梯式时提高工作频率和电子注效率是一个良好的途径。     

文学史对“发乎情，止乎礼义”诗教的依违——《（管锥编）艺理引义》之一

儒家“发乎情,止乎礼义”诗教,对后世的文学创作和文学批评都有很大影响。但对于该理论的接受,一直存在依违之分,在“发乎情”与“止乎礼义”两端,各有倚重。     

Plug-in estimators for the mean value and variance functions in delayed renewal processes

Abstract

In this paper, we deal with the problem of estimating the delayed renewal and variance functions in delayed renewal processes. Two parametric plug-in estimators for these functions are proposed and their unbiasedness, asymptotic unbiasedness and consistency properties are investigated. The asymptotic normality of these estimators are established. Further, a method for the computation of the estimators is given. Finally, the performances of the estimators are evaluated for small sample sizes by a simulation study.     

Improved inference for the shape-scale family of distributions under type-II censoring

The presence of a nuisance parameter may often perturb the quality of the likelihood-based inference for a parameter of interest under small to moderate sample sizes. The article proposes a maximal scale invariant transformation for likelihood-based inference for the shape in a shape-scale family to circumvent the effect of the nuisance scale parameter. The transformation can be used under complete or type-II censored samples. Simulation-based performance evaluation of the proposed estimator for the popular Weibull, Gamma and Generalized exponential distribution exhibits markedly improved performance in all types of likelihood-based inference for the shape under complete and type-II censored samples. The simulation study leads to a linear relation between the bias of the classical maximum likelihood estimator (MLE) and the transformation-based MLE for the popular Weibull and Gamma distributions. The linearity is exploited to suggest an almost unbiased estimator of the shape parameter for these distributions. Allied estimation of scale is also discussed.     

Asymptotic results in gamma kernel regression

Abstract

Based on the Gamma kernel density estimation procedure, this article constructs a nonparametric kernel estimate for the regression functions when the covariate are nonnegative. Asymptotic normality and uniform almost sure convergence results for the new estimator are systematically studied, and the finite performance of the proposed estimate is discussed via a simulation study and a comparison study with an existing method. Finally, the proposed estimation procedure is applied to the Geyser data set.