Localized algorithms for vlsi processor arrays

In this paper we analyze the algorithms expressed as a system of recurrence equations. The algorithms are called 2^?1 output algorithms if two output values of one function (variable identification) are specified by the system of recurrence equations for each index point in the algorithm. The algorithm is in free form if the indexes of these two values are not dependent. Two standard classes are determined by this criteria: the nearest neighbour and the all pair form. For example the sorting algorithm can be expressed in the all pair form i.e., the linear insertion algorithm or in the nearest neighbour form i.e., the bubble sort algorithm. However these algorithms are different in their nature. A procedure to eliminate the computational broadcast for the all pair 2^?1output algorithm has been proposed by the authors in [1]. The result obtained by implementing this procedure was a localized form of the algorithm and a system of uniform recurrence equations by eliminating the computational and data broadcast. So he data dependence method can be efficiently used for parallel implementations. The proposed procedure cannot be implemented directly on the nearest neighbour form algorithms. Here we show how the algorithm can be restructured into a form where the computational and data broadcast can be eliminated. These transformations result in localized algorithms. A few examples show how these algorithms can be implemented on processor arrays. For example, the Gentleman Kung triangular array [2] can be used for solving the QR decomposition algorithm for both forms of the algorithm. The implementations differ in the order of the data flow and the processor operation. We show that the implementation of the nearest neighbour algorithm is even better than the standard one.     

Algorithm transformations for the data broadcast elimination method

VLSI technology has had tremendous success in revolutionizing computer design with processor arrays. Local communication and interconnection is a constraint that dictates the design of processor arrays. The shared bus and global access to memory are now no longer used, since they lower the speed. Consequently, parallel algorithms must be designed according to these constraints.

One of the problems that must be resolved for the above mentioned constraints is data broadcast elimination. Algorithms must be transformed into a form that uses data propagation instead of data broadcast.

Here systems of affine recurrence equations are analyzed and data broadcast is denned in context of the definition of data dependence and affine recurrence equations. A method for data broadcast elimination is introduced in [1] and expands the system of affine recurrence equations into new recurrence equations, that define data propagation and eliminates the data dependences where data broadcast occurs.

Parallel algorithms are usually given as a set of similar tasks repetitively performed on different data. The iteration form of presenting the algorithms is most common. Several techniques are introduced to transform the algorithm to a single assignment form of recurrence equations.

Some improvements of these techniques are presented to make the application of the data broadcast elimination method easier and more straight forward. The presented techniques are classified as the transformation of iterative algorithms to a recurrence form, the transformation of recurrence form to a single assignment form, and fulfilling the index forms of the algorithms.

A system of affine recurrence equations with the data broadcast property is always obtained by applying these procedures. The method of data broadcast elimination successfully transforms this system of affine recurrence equations into a system of uniform recurrence equations which can be used for parallel implementation on VLSI processor arrays.     

基于QR分解的RLS算法及在扩频系统的应用研究

相对于扩频系统抑制窄带干扰的时域经典自适应滤波算法,基于QR分解的窄带干扰抑制方法是一种性能优良的新算法.研究了基于QR分解的RLS自适应滤波算法,考虑两种指数加权递归最小二乘(RLS)估计的算法--QR-RLS算法和逆QR-RLS算法,对扩频通信系统进行窄带干扰抑制.通过定义新的数据矩阵,该算法求解出数据域正规方程中的系数矩阵和右侧向量,从而提高了计算效率.最后用Matlab仿真了自适应滤波过程,仿真结果表明,该算法具有良好的计算性能以及收敛性能.     

Double pipelines and fast systolic designs on linear arrays

The fast systolic computation and double pipelines were designed to achieve implementations that use less processors to execute the algorithm in less time then the conventional systolic algorithms. H. T. Kung and C. S. Leiserson in [1-3] proposed systolic algorithms realized on a bidirectional linear array where two data streams flow in opposite directions. The data flow introduced for this solution requires data elements to appear in the data stream at each second time step, which is the only way to meet all the elements from the other data stream.

In [4, 5] the authors proposed a linear array where one data stream is double mapped while the elements from the other data stream flow in consecutive time moments. The procedure to obtain such a solution is called a fast systolic design. It was shown in [5] that double pipeline solutions are obtained by separating and grouping techniques in addition to this design.

Several more efficient systolic designs have been proposed for the matrix vector multiplication algorithm in [4, 5]. Here we implement these techniques on other linear array algorithms such as triangular linear system solver, string comparison, convolution, correlation, MA and AR filter.     

Analysis of the Kalman filter based estimation algorithm: an orthogonal decomposition approach

In this paper we shall provide new analysis on some fundamental properties of the Kalman filter based parameter estimation algorithms using an orthogonal decomposition approach based on the excited subspace. A theoretical analytical framework is established based on the decomposition of the covariance matrix, which appears to be very useful and effective in the analysis of a parameter estimation algorithm with the existence of an unexcited subspace. The sufficient and necessary condition for the boundedness of the covariance matrix in the Kalman filter is established. The idea of directional tracking is proposed to develop a new class of algorithms to overcome the windup problem. Based on the orthogonal decomposition approach two kinds of directional tracking algorithms are proposed. These algorithms utilize a time-varying covariance matrix and can keep stable even in the case of unsufficient and/or unbounded excitation.     

改进的APRIORI算法在试卷系统数据挖掘中的应用

本文通过对数据挖掘技术的研究,采用关联规则法对学生答题数据进行分析,并在关联规则使用中采用改进型的Apriori算法进行运算,构建高频集,并对于高分学生和低分学生的试卷进行了加权处理,使得高频集中的试题在知识点和难度上的关联更加突出,便于在自动组卷时更科学地评价试卷.     

An algorithm to compute the Wedderburn decomposition of semisimple group algebras implemented in the GAP package wedderga

We present an algorithm to compute the Wedderburn decomposition of semisimple group algebras based on a computational approach of the Brauer–Witt theorem. The algorithm was implemented in the GAP package wedderga.     

The computational complexity of approximating the minimal perturbation scaling to achieve instability in an interval matrix

An interval matrix can be represented in terms of a center matrix and a nonnegative error matrix, specifying maximum elementwise perturbations from the center matrix. A commonly proposed robust stability (regularity) characterization for an interval matrix with a stable (nonsingular) center matrix identifies the minimum scaling of this error matrix for which instability (singularity) is achieved. In this paper it is shown that approximating this minimum scaling is a MAX-SNP-hard problem. This implies that in the general case, unless the class of deterministic polynomial-time decision problems, P, equals the class of nondeterministic polynomial-time decision problems, NP, thought to be highly unlikely, this minimum scaling cannot be approximated with a ratio arbitrarily close to unity in polynomial time.This research was supported by the National Science Foundation under Grant ECS-8857019.     

Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model

The reduction of viral load is frequently used as a primary endpoint in HIV clinical trials. Nonlinear mixed-effects models are thus proposed to model this decrease of the viral load after initiation of treatment and to evaluate the intra- and inter-patient variability. However, left censoring due to quantification limits in the viral load measurement is an additional challenge in the analysis of longitudinal HIV data. An extension of the stochastic approximation expectation-maximization (SAEM) algorithm is proposed to estimate parameters of these models. This algorithm includes the simulation of the left-censored data in a right-truncated Gaussian distribution. Simulation results show that the proposed estimates are less biased than the usual naive methods of handling such data: omission of all censored data points, or imputation of half the quantification limit to the first point below the limit and omission of the following points. The viral load measurements obtained in the TRIANON-ANRS81 clinical trial are analyzed with this method and a significant difference is found between the two treatment groups of this trial.     

Contrast control for grey-level deformation removal in images: an algorithm and a computer application

An algorithm and a computer routines library written in object programming language C++ are described, which allow removal of global intensity deformation in a grey-scale image using contrast control. During the process, a Gaussian pyramid representation of an input image is constructed through low-pass filtration and sampling of successive pyramid levels, where the input image constitutes the first (zero) level of the pyramid. In the second step a Laplacian pyramid is built by subtracting successive levels of the Gaussian pyramid. Then, all levels in the Laplacian pyramid are expanded to the original image size and added with weights, which are real numbers, to reconstruct the image. Proper choice of the weights allows global grey-level deformation removal. This technique can be applied for contrast enhancement and image archiving of airborne, scanned, photo-copied and optical camera-made images, where global distortions of intensity are frequently met.     

An improved algorithm for finding community structure in networks with an application to IPv6 backbone network

The discovery of community structure in a large number of complex networks has attracted lots of interest in recent years. One category of algorithms for detecting community structure, the divisive algorithms, has been proposed and improved impressively. In this paper, we propose an improved divisive algorithm, the basic idea of which is to take more than one parameters into consideration to describe the networks from different points of view. Although its basic idea appears to be a little simple, it is shown experimentally that it outperforms some other algorithms when it is applied to the networks with a relatively obscure community structure. We also demonstrate its effectiveness by applying it to IPv6 backbone network. The communities detected by our algorithm indicate that although underdeveloped compared with IPv4 network, IPv6 network has already exhibited a preliminary community structure. Moreover, our algorithm can be further extended and adapted in the future. In fact, it suggests a simple yet possibly efficient way to improve algorithms.     

灰度投影在块匹配算法中的应用

运动参数估计在图像配准,电子稳像以及图像拼接中起着很重要的作用,其中块匹配算法是经常使用的一种方法。当平移较大的时候,块匹配算法仍然存在不足,因此本文提出了一种新的算法。首先利用灰度投影法得到相邻两幅图像的平移量,在此基础上再利用块匹配算法进行分块处理。实验说明了此方法的有效性,能够满足一般要求。     

Improved Alopex-based evolutionary algorithm by Gaussian copula estimation of distribution algorithm and its application to the Butterworth filter design

The application of evolutionary algorithms (EAs) is becoming widespread in engineering optimisation problems because of their simplicity and effectiveness. The Alopex-based evolutionary algorithm (AEA) possesses the basic characteristics of heuristic search algorithms but is lacking in adequate information about the fitness landscape of the input domain, reducing the convergence speed. To improve the performance of AEA, the Gaussian copula estimation of distribution algorithm (EDA) is embedded into the original AEA in this paper. With the help of Gaussian copula EDA, precise probability models are built utilising the best solutions, which can increase the convergence speed, and at the same time, keep the population diversity as much as possible. The simulation results on the benchmark functions and the application to the Butterworth filter design demonstrate the efficiency and effectiveness of the proposed algorithm, compared with several other EAs.     

Formalization of interrelations between operators and data within the framework of an extended algebra of algorithms

A system of algorithmic algebras is considered whose basic concepts are newly interpreted to formalize the interrelation between operators and data of such a system. A modified formal instrument is constructed that extends the possibilities of design and transformation of regular schemes of algorithms. Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 170–182, November–December 2008.     

An application to detect the edge and texture of the flower by canny algorithm

For the edge and texture characteristics of the flower, a new improved canny algorithm is proposed. In the method, canny algorithm detects the edge and the texture of the flower perfectly, the image noise is eliminated simultaneously. The method is applied to all bloom stages. The growing status of the flower could be better analyzed.     

蚂蚁算法在数据网格副本选择中的应用研究

数据网格中由于采用复制备份策略,文件存在多个副本.用户访问文件时,如何从拥有相同文件的多个结点中选择某一结点获取文件,达到以相同的代价获得最优质的服务,是一个迫切需要研究的问题.深入研究了蚂蚁算法的原理,分析了影响副本选择性能的主要因素,利用这些参考因素设计了基于蚂蚁算法的副本选择策略;并对这个新算法进行了分析和实现.经仿真平台实验,表明该算法可有效地减少数据访问延迟及带宽消耗,实现网格中存储节点间的负载平衡,提高数据的访问速度.     

Analysis of the blanket algorithm to study the texture of an image

We analyse the algorithm proposed by Pentland and show how to fit it to each image, choosing (efficiently) the number of interactions automatically. Furthermore, we discuss the possibilities and some disadvantages in the use of this algorithm for the computation of textures in real images.     

应用遗传算法构建化学模式分类器

神经网络和统计分析所构建的分类器均为复杂算式,难以体现专业知识;而分类规则直接以属性值为条件,确定个体类别,易于专业分析。对于连续属性的样本数据,本文应用基于信息熵的Chi-merge方法将其离散化,并将提取最优规则转换为组合优化问题,进而采用遗传算法求解。为此,本文将规则提取演绎为种群进化,并设计了个体适应度函数。由此提取出最优的分类规则,经过修剪处理后,与判别准则一起构成模式分类器。本文将其应用于橄榄油产地判别,所建立的分类器简单明了,规则数少,性能良好,适用于化学模式分类。