非线性RL电路的暂态特性

对一个可解的非线性ＲＬ电路模型的暂态过程进行了研究，得到非线性ＲＬ电路的一些普遍特性，加深了加ＲＬ电路中的有关概念的理解，对教学有一定的参考价值。     

关于Lipschitz强增生算子的迭代程序

本文在一般的Ｂａｎａｃｈ空间中讨论Ｌｉｐｓｃｈｉｔｚ强增生算子方程解和严格伪压缩算子不动点的迭代逼近问题．我们的结果统一和推广了Ｄｅｎｇ，Ｌｉｕ，Ｔａｎ和Ｘｕ的结果，完整地回答了Ｃｈｉｄｕｍｅ提出的公开问题．     

一类新的k-次增生型变分包含解的存在性及其具有混合误差项的Ishikawa迭代逼近

在实自反Banach空间中,引入和研究了一类新的k-次增生型变分包含问题,证明了这类变分包含解的存在性、唯一性及其具有混合误差项的Ishikawa迭代程序的收敛性.本文结果本质地改进、发展和统一了张石生和曾六川等人的一系列相关结果.     

A statistical process control approach to selecting a warm-up period for a discrete-event simulation

The selection of a warm-up period for a discrete-event simulation continues to be problematic. A variety of selection methods have been devised, and are briefly reviewed. It is apparent that no one method can be recommended above any other. A new approach, based upon the principles of statistical process control, is described (SPC method). Because simulation output data are often highly autocorrelated and potentially non-normal, the batch means method is employed in constructing the control chart. The SPC method is tested on seven data sets and encouraging results are obtained concerning its accuracy. The approach is also discussed with respect to its ease of implementation, simplicity, generality of use and requirements for parameter estimation.     

报酬无界的平均准则马氏决策过程

本文对可数状态集、非空决策集、报酬无界的平均准则马氏决策过程，提出了一组新的条件，在此条件下存在（ε）最优平稳策略，且当最优不等式中的和有定义时最优不等式也成立。     

A different construction of Gaussian fields from Markov chains: Dirichlet covariances

We study a class of Gaussian random fields with negative correlations. These fields are easy to simulate. They are defined in a natural way from a Markov chain that has the index space of the Gaussian field as its state space. In parallel with Dynkin's investigation of Gaussian fields having covariance given by the Green's function of a Markov process, we develop connections between the occupation times of the Markov chain and the prediction properties of the Gaussian field. Our interest in such fields was initiated by their appearance in random matrix theory.     

A PARALLEL COMPUTATION SCHEME FOR IMPLICIT RUNGE-KUTTA METHODS AND THE ITERATIVELY B-CONVERGENCE OF ITS NEWTON ITERATIVE PROCESS

In this paper, based on the implicit Runge-Kutta(IRK) methods, we derive a class of parallel scheme that can be implemented on the parallel computers with Ns(N is a positive even number) processors efficiently, and discuss the iteratively B-convergence of the Newton iterative process for solving the algebraic equations of the scheme, secondly we present a strategy providing initial values parallelly for the iterative process. Finally, some numerical results show that our parallel scheme is higher efficient as N is not so large.     

氏调制的几何布朗运动与布林带

在证券市场, 布林带作为流行的技术分析工具被广泛的运用\bd 到目前为止有许多模型被建立用来预测证券的价格, 因此研究这些模型是否具有布林带性质是一个重要的问题\bd Liu, Huang and Zheng (2006)和Liu and Zheng (2006)分别讨论了Black-Scholes模型和随机波动率模型作为真实的股票市场的布林带, 并且证明了相应的统计量的平稳性和大数定律成立\bd 本文我们将上述结果推广到马氏调制的几何布朗运动模型.     

Kernel regression estimation for continuous spatial processes

We investigate here a kernel estimate of the spatial regression function r(x) = E(Y _u | X _u = x), x ∈ ℝ^d, of a stationary multidimensional spatial process { Z _u = (X _u, Y _u), u ∈ ℝ ^N }. The weak and strong consistency of the estimate is shown under sufficient conditions on the mixing coefficients and the bandwidth, when the process is observed over a rectangular domain of ℝ^N. Special attention is paid to achieve optimal and suroptimal strong rates of convergence. It is also shown that this suroptimal rate is preserved by using a suitable spatial sampling scheme.