半序度量空间中公共二元随机重合点定理及其应用

在完备可分的半序度量空间中,引入了随机映射对(F,G)关于g随机半序弱增以及(F,G)随机半序弱增的定义,研究了在满足一定非线性压缩条件下的随机映射列F_k:Ω×X×X→X,k=1,2…,g:Ω×X→X和h:Ω×X→X的公共二元随机重合点与公共二元随机不动点问题,所得结果推广了已有文献中的一些不动点定理.     

Continuous-Time Independent Edge-Markovian Random Graph Process

In this paper, the continuous-time independent edge-Markovian random graph process model is constructed. The authors also define the interval isolated nodes of the random graph process, study the distribution sequence of the number of isolated nodes and the probability of having no isolated nodes when the initial distribution of the random graph process is stationary distribution, derive the lower limit of the probability in which two arbitrary nodes are connected and the random graph is also connected, and prove that the random graph is almost everywhere connected when the number of nodes is sufficiently large.     

Complete Convergence for Weighted Sums of Arrays of Rowwise Asymptotically Almost Negative Associated Random Variables

Let be an array of rowwise asymptotically almost negative associated (AANA, in short) random variables. The complete convergence for weighted sums of arrays of rowwise AANA random variables is established under some general moment conditions. The result obtained in the paper generalizes and improves the corresponding one for negatively associated random variables.     

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??A class of backward doubly stochastic differential equations driven by white noises and Poisson random measures are studied in this paper. The definitions of solutions and Yamada-Watanabe type theorem to this equation are established.     

基于人工神经网络和随机游走模型的汇率预测

由于金融数据具有随机性特征,使得建模和预测变得极其困难.提出一种组合预测方法,即假定任何金融时序数据由线性和非线性两部分组成,将其中线性部分的数据通过随机游走(RW)模型进行模拟,剩余的非线性残差部分由前馈神经网络(FANN)和诶尔曼神经网络(EANN)协同处理.从实证结果可知,该组合方法相比单独使用RW、FANN或EANN模型有更高的预测精度.     

Random walks on stochastic hyperbolic half planar triangulations

We study the simple random walk on stochastic hyperbolic half planar triangulations constructed in (Angel and Ray, Ann Probab, in press). We show that almost surely the walker escapes the boundary of the map in positive speed and that the return probability to the starting point after n steps scales like © 2016 Wiley Periodicals, Inc. Random Struct. Alg., 49, 213–234, 2016     

Calculating ellipse area by the Monte Carlo method and analysing dice poker with Excel at high school

This paper reports on lessons in which 18–19 years old high school students modelled random processes with Excel. In the first lesson, 26 students formulated a hypothesis on the area of ellipse by using the analogy between the areas of circle, square and rectangle. They verified the hypothesis by the Monte Carlo method with a spreadsheet model developed in the lesson. In the second lesson, 27 students analysed the dice poker game. First, they calculated the probability of the hands by combinatorial formulae. Then, they verified the result with a spreadsheet model developed in the lesson. The students were given a questionnaire to find out if they found the lesson interesting and contributing to their mathematical and technological knowledge.     

A randomized first-passage problem for drifted Brownian motion subject to hold and jump from a boundary

We study an inverse first-passage-time problem for Wiener process X(t) subject to hold and jump from a boundary c. Let be given a threshold S > X(0) ≥ c, and a distribution function F on [0, +∞). The problem consists in finding the distribution of the holding time at c and the distribution of jumps from c, so that the first-passage time of X(t) through S has distribution F.     

A scalable pairwise class interaction framework for multidimensional classification

We present a general framework for multidimensional classification that captures the pairwise interactions between class variables. The pairwise class interactions are encoded using a collection of base classifiers (Phase 1), for which the class predictions are combined in a Markov random field that is subsequently used for multidimensional inference (Phase 2); thus, the framework can be positioned between multilabel Bayesian classifiers and label transformation-based approaches. Our proposal leads to a general framework supporting a wide range of base classifiers in the first phase as well as different inference methods in the second phase. We describe the basic framework and its main properties, as well as strategies for ensuring the scalability of the framework. We include a detailed experimental evaluation based on a range of publicly available databases. Here we analyze the overall performance of the framework and we test the behavior of the different scalability strategies proposed. A comparison with other state-of-the-art multidimensional classifiers show that the proposed framework either outperforms or is competitive with the tested straw-men methods.     

超深亚微米互补金属氧化物半导体器件的剂量率效应

对0.18 μm互补金属氧化物半导体(CMOS)工艺的N型金属氧化物半导体场效应晶体管(NMOSFET)及静态随机存储器(SRAM)开展了不同剂量率下的电离总剂量辐照试验研究. 结果表明: 在相同累积剂量, SRAM的低剂量率辐照损伤要略大于高剂量率辐照的损伤, 并且低剂量率辐照损伤要远大于高剂量率辐照加与低剂量率辐照时间相同的室温退火后的损伤. 虽然NMOSFET 低剂量率辐照损伤略小于高剂量率辐照损伤, 但室温退火后, 高剂量率辐照损伤同样要远小于低剂量率辐照损伤. 研究结果表明0.18 μm CMOS工艺器件的辐射损伤不是时间相关效应. 利用数值模拟的方法提出了解释CMOS器件剂量率效应的理论模型.