An effective step-down algorithm for the construction and the identification of nonisomorphic orthogonal arrays

In this paper we present an effective algorithm for the construction and the identification of two-level nonisomorphic orthogonal arrays. Using this algorithm, we identify and list a full catalogue of nonisomorphic orthogonal arrays with parameters OA(24,7,2,t), OA(28,6,2,t) and OA(32,6,2,t), t ≥ 2. Some statistical properties of these designs are also considered.     

18-run nonisomorphic three level orthogonal arrays

In this paper we construct all possible orthogonal arrays OA(18,q, 3,2) with 18 runs and 3 ≤ q ≤ 7 columns and present those that are nonisomorphic. A discussion on the novelty and the superiority of many of the designs found in terms of isomorphism and generalized minimum aberration has been made.      

阵列除法器的FPGA实现

先对除法器运算进行了分析,然后用FPGA实现了两种常见的结构硬件除法器,并分析了先行进位阵列除法器的设计原理。     

Some orthogonal arrays with 32 runs and their projection properties

Screening designs are useful for situations where a large number of factors are examined but only a few, k, of them are expected to be important. Traditionally orthogonal arrays such as Hadamard matrices and Plackett Burman designs have been studied for this purpose. It is therefore of practical interest for a given k to know all the classes of inequivalent projections of the design into the k dimensions that have certain statistical properties. In this paper we present 15 inequivalent Hadamard matrices of order n=32 constructed from circulant cores. We study their projection properties using several well-known statistical criteria and we provide minimum generalized aberration 2 level designs with 32 runs and up to seven factors that are embedded into these Hadamard matrices. A concept of generalized projectivity and design selection of such designs is also discussed.AMS Subject Classification: Primary 62K15, Secondary 05B20     

Optimal designs under two related models for interference

We consider two related models for interference: one having different directional neighbour effects and one with the same neighbour effects. We show that optimal designs for one model can be obtained from optimal designs for the other model. Acknowledgement. We are grateful to H. Kushner for advance notice of his work. SP was supported by the Isfahan University of Technology, Iran.     

红外监测三坐标平移动物实验台的研制

演化硬件研究将进化思想应用于电子系统内部结构的设计和调整,以实现硬件电路的自组织、自适应和自修复,从而提高系统的可靠性。介绍了演化硬件的概念、基本原理和实现方法,对国内外研究动态及已取得的成果进行了总结,并指出了目前研究存在的主要问题。     

短波MIMO通信的研究进展

短波通信中的天波传播信道因为多径和多模式传播而具有充分散射的特征,因而非 常适合多输入多输出技术的应用。总结了短波多输入多输出技术通信的研究现状,归纳并分 析了 短波多输入多输出技术本身以及间隔式同构天线阵和同位置异构天线阵在短波多输入多输出 通信中应用的可行性,并指出了需要进一步解决的问题。     

Optimal nested row-column designs for blocks of size 2×2 under dependence

This paper examines nested 2 ×2 row-column designs when within-block observations are assumed to be dependent. The model considered has fixed block effects, which may also include row and/or column effects. Optimal binary and non-binary designs, constructed from semi-balanced arrays, are given under both generalised and ordinary least squares estimation. It is shown that binary designs are optimal when dependence is low. In general, however, the optimal designs are highly specific to the correlation values. Received: October 1999     

迭代投影的平顶方向图综合算法

针对现有的平顶波束综合形成算法计算量较大的问题，提出了一种迭代求解平顶波束的快速形成算法。该算法首先设置方向图参数、迭代条件，然后利用方向图与阵元加权系数的变换关系设计投影算法并通过二阶差分运算确定过渡带，最后结合蝶形计算方法快速迭代逼近理想的平顶方向图。实验结果表明，该算法相比凸优化算法运算效率较高，并且可修复阵元失效后的平顶方向图。算法运算次数随着副瓣阈值、主瓣宽度和零陷深度等参数的变化而变化。     

A new family of bivariate max-infinitely divisible distributions

In this article we discuss the asymptotic behaviour of the componentwise maxima for a specific bivariate triangular array. Its components are given in terms of linear transformations of bivariate generalised symmetrised Dirichlet random vectors introduced in Fang and Fang (Statistical inference in elliptically contoured and related distributions. Allerton Press, New York, 1990). We show that the componentwise maxima of such triangular arrays is attracted by a bivariate max-infinitely divisible distribution function, provided that the associated random radius is in the Weibull max-domain of attraction.