集群计算机上基于BSP模型的并行算法及其程序设计

文章分析了BSP模型和集群计算机的特点，给出了在集群计算机根据BSP模型设计并行算法及其软件的原则，举例说明了利用BSP模型代价公式定性分析并行算法性能的方法，并利用实验结果验证了得出的结论。结果表明模型的成功地抽象出了集群计算中影响算法性能的诸种因素，并通过代价公式反映出来，利用代价公式可以基本准确地估计并行算法代价，这对集群计算机上的并行算法及其软件及设计和优化具有重要的指导意义。     

Stochastic signal analysis: Numerical representation and applications to system theory

Alternative procedures for representing a stochastic signal as a denumerable series with uncorrelated terms are developed. The study includes considerations about parametric rescaling and its repercussions on the orthogonal expansion, as well as numerical techniques for approaching such an expansion. In addition, applications to the Gaussian characterization of stochastic signals, filtering and stochastic modelling are treated.     

A Genetic Search for Exploiting a Fuzzy Preference Model of Portfolio Problems with Public Projects

When an organization solves a portfolio problem with public projects evaluated by multiple criteria, in which the economic dimension is not essential or not well characterized, the classical methods are not useful. We propose a non-linear preference model developed from normative Value Theory and using fuzzy sets to model some sources of imprecision. This model can be considered as a generalization of the classical approaches. However, the optimization problem is very complex in order to be solved with non-linear programming techniques. Therefore, the model is exploited by an evolutionary algorithm, able to achieve a strong improvement of the quality of solution.     

Toward Fuzzy Optimization without Mathematical Ambiguity

Fuzzy programming has been discussed widely in literature and applied in such various disciplines as operations research, economic management, business administration, and engineering. The main purpose of this paper is to present a brief review on fuzzy programming models, and classify them into three broad classes: expected value model, chance-constrained programming and dependent-chance programming. In order to solve general fuzzy programming models, a hybrid intelligent algorithm is also documented. Finally, some related topics are discussed.     

第三代短波自动链路建立系统特性分析及仿真实现

分析了第三代短波自动链路建立系统的工作特性及技术特点，并对系统仿真实现的原则及一些细节问题进行了较深入的探讨，同时对仿真实现中涉及的链路质量分析（LQA）算法进行了研究。     

有界变量线性规划的基线算法

本文对有界变量线性规划的算法进行了研究，得到了一种解此问题的新算法。文中根据基线算法的算法原理，通过对BL表的旋转，在各变量满足界约束的条件下，使目标函数值不断增大，直至得到有界硬上界，从而得到问题的最优解。文中给出了有界变量线性规划基线算法的计算步骤，并给出了一个例子。与单纯形法相比，采用基线算法解有界变量线性规划操作更简单。迭代次数少，解题速度更快。     

An admissible minimax estimator of a bounded scale-parameter in a subclass of the exponential family under scale-invariant squared-error loss

A subclass of the scale-parameter exponential family is considered and for the rth power of the scale parameter, which is lower bounded, an admissible minimax estimator under scale-invariant squared-error loss is presented. Also, an admissible minimax estimator of a lower-bounded parameter in the family of transformed chi-square distributions is given. These estimators are the pointwise limits of a sequence of Bayes estimators. Some examples are given.     

一种在Kalman滤波中引入径向速度测量的新方法

研究在距离和径向速度测量噪声统计相关的情形下把径向速度测量引入Kalman滤波的新方法。分析了径向速度测量噪声与位置测量更新后状态滤波误差的统计相关性,根据Gauss-Markov定理导出了对应于径向速度测量的滤波方程由此而得到一种序贯滤波算法。两个不同的蒙特卡罗仿真表明,通过采用这一新算法引人径向速度测量,不仅可以大大提高状态估计的精度,而且其估计性能和计算效率优于传统的EKF。     

平行机半在线排序问题研究(Ⅰ)

对半在线平行机排序问题的研究进展作了详细综述和进一步探讨。文章给出半在线排序问题的背景、定义、分类和求解。介绍它们定义和在不同机器环境和目标函数下半在线排序问题分类，以及第一类半在线模型的近似算法的设计及其竞争比分析。     

Statistical Inference with Fractional Brownian Motion

We give a test between two complex hypothesis; namely we test whether a fractional Brownian motion (fBm) has a linear trend against a certain non-linear trend. We study some related questions, like goodness-of-fit test and volatility estimation in these models.