微生物代谢过程中的一类差分方程正解的渐近性

研究描述微生物代谢过程中虫口变化规律的一类差分方程 ,获得了保证其每一正解趋于正平衡点的一族充分条件 ,改进和推广了已有的结果 .     

An alternative approach to multivariate EWMA control chart

This Paper proposes a multivariate EWMA scheme that is alternative to the traditional EWMA-M. The distribution of the chart statistic is derived from Box quadratic form and the sensitivity of the chart is examined. The average run lengths of the M-EWMA scheme are numerically computed with the integral equation method. The exponential weight of 0.2 is found to be the optimal choice for the sensitive chart to detect assignable causes in the mean vector of processes.     

浅谈问题繁殖和知识增长

本文受文献［４］ 的启发，在文献［５］ 的基础上，根据科学问题的“雪崩”式繁殖与原子反应堆中核裂变时中子扩散过程之间的类比，引用物质扩散方程导出了科学问题增长方程，统一说明了普赖斯曲线和逻辑斯蒂曲线的数学表达式，并阐明普赖斯———纳林莫夫曲线数学表达式中角变量的本质．表明角变量是反映社会影响作用的，在一定程度上，指数增长律的背景曲线上的波动现象可由此解释．     

新型同轴慢波结构特性的研究

为了克服因增加返波管功率容量而引起的模式竞争问题,提出了波纹内导体同轴慢波结构,导出了该结构在冷腔时的TM0n模式色散方程,并数值计算和分析了该结构的色散特性。分析结果表明:采用该结构的返波管能够很好地改善模式竞争。     

Optimal stopping for Brownian motion with applications to sequential analysis and option pricing

Herman Chernoff made fundamental contributions to analytical and computational methods for solving optimal stopping problems for Brownian motion. He also showed how these optimal stopping problems are closely related to some basic problems in sequential analysis and singular stochastic control. This paper gives a survey of these and related developments and describes some recent applications to option valuation in financial economics.     

具任意次幂非线性项的组合KdV方程和广义Boussinesq方程的精确解

本文求解了具任意次幂非线性项的组合K dV方程ut aupux bu2pux δuxxx=0和广义Boussinesq方程utt x(ux aupux bu2pux ruxx δuxxx)=0的若干精确孤立波解.通过适当变换,并结合待定系数法和计算机代数系统M athem atica求出了它们的钟状和扭状精确孤立波解.     

关于混合酸中各组分同时测定的研究(Ⅰ)

研讨了甲酸、乙酸混合酸中两组分同时测定的终点计算问题，提出的数学模型对其它混合酸各组分的同时测定具有普遍意义     

磁致伸缩作动器连续模型辨识

提出了一种采样数据中存在高频有色噪声的连续模型辨识方法,并将其应用到磁致伸缩作动器的连续模型辨识中。该方法通过引入积分运算,将连续时间系统的微分方程转换为积分方程,从而使噪声的影响可以忽略,直接利用传统的最小二乘法估计出连续时间模型。仿真实例验证了该方法的有效性和可行性,辨识的磁致伸缩作动器具有较高的可信度。     

Simultaneous Confidence Bands and Hypothesis Testing in Varying-coefficient Models

Regression analysis is one of the most commonly used techniques in statistics. When the dimension of independent variables is high, it is difficult to conduct efficient non-parametric analysis straightforwardly from the data. As an important alternative to the additive and other non-parametric models, varying-coefficient models can reduce the modelling bias and avoid the "curse of dimensionality" significantly. In addition, the coefficient functions can easily be estimated via a simple local regression. Based on local polynomial techniques, we provide the asymptotic distribution for the maximum of the normalized deviations of the estimated coefficient functions away from the true coefficient functions. Using this result and the pre-asymptotic substitution idea for estimating biases and variances, simultaneous confidence bands for the underlying coefficient functions are constructed. An important question in the varying coefficient models is whether an estimated coefficient function is statistically significantly different from zero or a constant. Based on newly derived asymptotic theory, a formal procedure is proposed for testing whether a particular parametric form fits a given data set. Simulated and real-data examples are used to illustrate our techniques.     

用不动点定理研究方程解的存在性

介绍常用的不动点定理,并给出它在方程中有关解的存在问题的应用实例.