一类并行隐式Runge-Kutta方法的A稳定性分析

本文针对多处理机系统构造了一类并行隐式Runge—Kutta方法,给出了一个具有三阶精度的并行二级Runge—Kutta公式,并证明了该计算公式具有A稳定性,数值结果表明该计算公式对求解刚性常微分方程是有效的。     

波束域Root-MUSIC算法的进一步降阶处理

研究了波束域降阶Root-MUSIC算法，在子阵分解降阶的基础上，进一步将多项式的求根阶次降到与源数目相同，提出了求解降阶多项式的方法。该方法最大程度地减少了求根多项式的阶次和求解多项式的次数，并保持了Root—MUSIC算法的优良性能。显著降低运算量是其最大优点，仿真结果验证了降阶算法的有效性，并比较了不同阶次波束域Root—MUSIC算法的估计性能。     

优化物流中心配送方案的遗传算法

提出了一种配送方案模型 ,该模型在满足车辆满载约束的同时充分考虑货物的运到期限 ,通过实例计算表明 ,该算法对确定配送装车方案是可行和有效的.     

Study on Optimal Topology for Computer Local Double Loop Networks

A dist ributed optimal local double loop (DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definitions and theorems are described and proved. An algorithm which can optimize the double loop networks is presented. The optimal values of the topologic parameters for the DOLDL have been obtained by the algorithm, and these numerical results are analyzed. The study shows that the bounds of the optimal diameter d and average hop distance a for this class of networks are [3N- 2]≤d≤[3N ] and (5N/9 (N-1))-(3N -1.8)相似文献   

A reduction algorithm for approximating a (nonmetric) dissimilarity by a tree distance

We propose a development stemming from Roux (1988). The principle is progressively to modify the dissimilarities so that every quadruple satisfies not only the additive inequality, as in Roux's method, but also all triangle inequalities. Our method thus ensures that the results are tree distances even when the observed dissimilarities are nonmetric. The method relies on the analytic solution of the least-squares projection onto a tree distance of the dissimilarities attached to a single quadruple. This goal is achieved by using geometric reasoning which also enables an easy proof of algorithm's convergence. This proof is simpler and more complete than that of Roux (1988) and applies to other similar reduction methods based on local least-squares projection. The method is illustrated using Case's (1978) data. Finally, we provide a comparative study with simulated data and show that our method compares favorably with that of Studier and Keppler (1988) which follows in the ADDTREE tradition (Sattath and Tversky 1977). Moreover, this study seems to indicate that our method's results are generally close to the global optimum according to variance accounted for.We offer sincere thanks to Gilles Caraux, Bernard Fichet, Alain Guénoche, and Maurice Roux for helpful discussions, advice, and for reading the preliminary versions of this paper. We are grateful to three anonymous referees and to the editor for many insightful comments. This research was supported in part by the GREG and the IA² network.     

An only-once-sorting algorithm

This paper provides a new sorting algorithm called “Only-Once-Sorting” algorithm. Using a mathematical formula, this algorithm can put elements in the positions they should be stored only once, then compacts them. The algorithm completes sorting a sequence ofn elements in a calculation time of O(n). Xu Xusong: born in June 1945. Professor. Current research interest is in data structure and algorithm, information systems analysis and design     

计算机时钟同步技术研究

首先介绍了和分析了计算机时钟同步系统的主要理论与技术，研究了同步系统的三个主要组成部分，然后研究了应用最为广泛的绝对物理时钟同步系统的设计方法，对其两种核心算法：CRI算法和PCS算法进行了详细的分析及性能比较，作为上述时钟同步理论的一个应用例子，本文最后简要介绍了基于网络时间协议（NTP）的同步技术及其软件实现。     

集成电路的电路模拟程序

PSCNT1.3是一个在微机上开发成功的集成电路模拟分析程序,具有需要内存少、运行速度快的特点,并有可靠的收敛性.本文较详细地介绍了使PSCNT1.3达到这样效果的主要算法:节点撕裂法、三极管的降阶算法、简化的稀疏矩阵技术,以及改进的牛顿迭代法等.本文还给出了一个应用此程序的计算实例.     

An error variance approach to two-mode hierarchical clustering

A new agglomerative method is proposed for the simultaneous hierarchical clustering of row and column elements of a two-mode data matrix. The procedure yields a nested sequence of partitions of the union of two sets of entities (modes). A two-mode cluster is defined as the union of subsets of the respective modes. At each step of the agglomerative process, the algorithm merges those clusters whose fusion results in the smallest possible increase in an internal heterogeneity measure. This measure takes into account both the variance within the respective cluster and its centroid effect defined as the squared deviation of its mean from the maximum entry in the input matrix. The procedure optionally yields an overlapping cluster solution by assigning further row and/or column elements to clusters existing at a preselected hierarchical level. Applications to real data sets drawn from consumer research concerning brand-switching behavior and from personality research concerning the interaction of behaviors and situations demonstrate the efficacy of the method at revealing the underlying two-mode similarity structure.