An Iterative Procedure for Evaluating Digraph Competitions

A competition which is based on the results of (partial) pairwise comparisons can be modelled by means of a directed graph. Given initial weights on the nodes in such digraph competitions, we view the measurement of the importance (i.e., the cardinal ranking) of the nodes as an allocation problem where we redistribute the initial weights on the basis of insights from cooperative game theory. After describing the resulting procedure of redistributing the initial weights, an iterative process is described that repeats this procedure: at each step the allocation obtained in the previous step determines the new input weights. Existence and uniqueness of the limit is established for arbitrary digraphs. Applications to the evaluation of, e.g., sport competitions and paired comparison experiments are discussed.     

The Likelihood of the Parameters of a Continuous Time Vector Autoregressive Model

This paper provides a method of constructing the likelihood function of the parameters of a continuous time vector autoregressive model on the basis of discrete data without requiring the restrictions extant methods impose on the data that are capable of being rejected by a statistical test. In particular, the method does not rely on a steady-state assumption that can rule out unit root processes; it allows for weak assumptions on the innovations; and it allows for a mixture of skip-sampled and temporally-aggregated data. This revised version was published online in August 2006 with corrections to the Cover Date.     

倒向随机微分方程及其应用

本文将介绍一类新的议程：倒向随机微分方程，为了便于理解，我们将首先通过与常微分方程和经典的随机微分方程的对比，并通过数理经济和数学金融学中的一个典型的例子来引入倒向随机微分方程。     

男上体运动变形与服装放松量的关系

对东北地区男青年体型进行了测量 ,建立了东北地区男青年人体模型。并选若干标准人体采用剪切变形法对男上装显著变形部位的变化方向及变化量进行了研究分析 ,得到男上装各主要部位适合人体正常运动所需的服装放松量。     

随机模糊神经网络及在随机混沌时间序列预测中的应用

针对随机模糊神经网络(SFNN)的网络结构没有明确的物理含义，仅仅是一种实现随机模糊逻辑系统的计算结构的问题，对其网络结构进行了改进，重新定义了每层的节点原型。改进后每层之间的物理含义明确且节点数目减少，从而计算量有所减少。对于SFNN的参数和结构，可以分别通过参数学习算法和结构学习算法来优化。将SFNN用于随机混沌时间序列预测，仿真结果表明：该系统由于引入了随机的概念，使网络能更有效地防止噪声的干扰，因而更适合于工程应用。     

Ergodic Properties of the Non-Markovian Langevin Equation

We discuss the dissipative dynamics of a classical particle coupled to an infinitely extended heat reservoir. We announce a number of results concerning the ergodic properties of this model. The novelty of our approach is that it extends beyond Markovian dynamics to the case where the Langevin equation is driven by colored noise. Our method works in arbitrary space dimension, and for fully nonlinear systems.     

Structure of a gasdynamic disturbance in a thermodynamically nonequilibrium medium with a power-law relaxation model

The evolution and the steady-state structure of gasdynamic disturbances in a thermodynamically nonequilibrium gas are investigated both analytically and numerically. It is shown that in a medium with negative viscosity steady-state structures different from those in an equilibrium medium can exist. The conditions of existence of stationary shock waves with a discontinuous front and a smooth increase or decrease in the amplitude behind the front, waves with an oscillatory structure, and a stationary self-wave pulse with a power-law trailing front are determined.Translated from Izvestiya Rossiiskoi Academii Nauk, Mekhanika Zhidkosti i Gaza, No. 5, 2004, pp. 181–191. Original Russian Text Copyright © 2004 by Makaryan and Molevich.     

二参数有限随机事件流

本文讨论二参数无后效有限随机事件流的鞅性和各种二参数Ｍａｒｋｏｖ性。     

Aspiration Based Simulated Annealing Algorithm

An aspiration based simulated annealing algorithm for continuousvariables has been proposed. The new algorithm is similar to the one givenby Dekkers and Aarts (1991) except that a kind of memory is introduced intothe procedure with a self-regulatory mechanism. The algorithm has beenapplied to a set of standard global optimization problems and a number ofmore difficult, complex, practical problems and its performance comparedwith that of the algorithm of Dekkers and Aarts (1991). The new algorithmappears to offer a useful alternative to some of the currently availablestochastic algorithms for global optimization.     

Regularity and convergence of stochastic convolutions in duals of nuclear Fréchet spaces

Let Φ′ be the strong dual of a nuclear Fréchet space Φ. In this paper we present regularity properties, weak convergence, and convergence in probability and in mean square of Φ′-valued stochastic evolution equations and convolutions with respect to Φ′-valued cadlag martingales.