Finding roots of a real polynomial simultaneously by means of Bairstow's method

Aberth's method for finding the roots of a polynomial was shown to be robust. However, complex arithmetic is needed in this method even if the polynomial is real, because it starts with complex initial approximations. A novel method is proposed for real polynomials that does not require any complex arithmetic within iterations. It is based on the observation that Aberth's method is a systematic use of Newton's method. The analogous technique is then applied to Bairstow's procedure in the proposed method. As a result, the method needs half the computations per iteration than Aberth's method. Numerical experiments showed that the new method exhibited a competitive overall performance for the test polynomials.     

On the rate of convergence of certain methods of centers

It is shown in this paper that a theoretical method of centers, introduced by Huard, converges linearly. It is also shown, by counter-example, that a modified method of centers due to Huard and a method of feasible direction due to Topkis and Veinot cannot converge linearly even under convexity assumptions. Because of this, a new modified method of centers is introduced which uses a quadratic programming direction finding subroutine. In most uses this new method is not more complicated than Huard's modified method of centers. But it does converge linearly. A method for implementing it without loss of rate of convergence is also discussed.Research sponsored by the Joint Services Electronics Program, Grant AF-AFOSR-68-1488 and the National Aeronautics and Space Administration, Grant NGL-05-003-016.     

研究伪随机数序列独立性的均匀偏度法

§1 引言 由具有在[0,1]上均匀分布的总体中产生的简单子样称为随机数序列,其中的每一样本称为随机数。所谓伪随机数序列,一般是指用数学递推公式所产生的随机数序列。如最常见的乘同余方法,它所产生的伪随机数序列就是对给定的正整数M和小于M的任意正整数初值β_1,用如下递推公式确定的:     

复合材料旋转壳非线性稳定性分析计算

利用前屈曲一致理论和能量变分法分析计算了复合材料旋转壳非线性稳定性.前屈曲应变-位移关系采用非线性的卡门方程,能量积分采用数值积分,用势能最小原理求解前屈曲位移和内力,提出了求解临界载荷的实用计算方法,用FORTRAN语言编制了相应的计算机程序,并给出了算例.     

Burgers方程的一类交替分组方法

对于Burgers方程给出了一组新的Saul'yev型非对称差分格式，并用这些差分格式构造了求解非线性Burgers方程的交替分组四点方法．该算法把剖分节点分成若干组，在每组上构造能够独立求解的差分方程．因此算法具有并行本性，能直接在并行计算机上使用．章还证明了所给算法线性绝对稳定．数值试验表明，该方法使用简便，稳定性好，有很好的精度。     

模糊决策综合评价法在职称评聘工作中的应用

在高等院校和科研院所 ,职称评聘工作是一项比较难的工作 .由于评聘中 ,许多指标具有模糊性 ,提出用模糊决策综合评价法进行职称评聘工作 ,将其定量化 ,使职称评聘工作更容易 ,并且尽量减少人为因素的干扰 ,是一种科学有效的方法 .     

渗流问题灰色数值模型的解法研究

灰色数值模型的求解是研究灰色数值模型的一个重要问题 .本文根据灰集合、灰数及其灰色运算规则 ,在渗流系统的基本灰色数值模型的基础上 ,分析了求解这类模型的一整套灰色数值算法 ,并对灰色数值算法、普通算法和经典数值方法的计算结果进行了全面比较 ,论证了灰色数值算法对灰信息传递的正确性和对渗流系统描述的合理性 .     

Accelerated Imaginary-time Evolution Methods for the Computation of Solitary Waves

Two accelerated imaginary-time evolution methods are proposed for the computation of solitary waves in arbitrary spatial dimensions. For the first method (with traditional power normalization), the convergence conditions as well as conditions for optimal accelerations are derived. In addition, it is shown that for nodeless solitary waves, this method converges if and only if the solitary wave is linearly stable. The second method is similar to the first method except that it uses a novel amplitude normalization. The performance of these methods is illustrated on various examples. It is found that while the first method is competitive with the Petviashvili method, the second method delivers much better performance than the first method and the Petviashvili method.     

ATOR迭代法的收敛性

本文定义了广义ATOR迭代法,并给出了该方法的Stein-Rosenberg型定理和Ostrows-ki-Reich型定理,广义ATOR方法的单调收敛界及其与SOR法的比较也在本文给予讨论。     

A Generalization of the Transportation Method of Linear Programming

The transportation method of linear programming is extended to a more general class of problem, for which the "stepping-stone method" of Charnes and Cooper fails. The method is applicable to various problems in the optimum scheduling of production and transport.This paper reviews the relevant theory, and then describes an efficient computational method, applicable to computers of moderate capacity. Many features of the transportation method are retained. In particular, the amount of information which must be retained, at each stage of calculation, is much less, for a large problem, than is required for the simplex or revised simplex methods.     

The Impact of Equal Weighting of Low- and High-Confidence Observations on Robust Linear Regression Computations

Equal weighting of low- and high-confidence observations occurs for Huber, Talwar, and Barya weighting functions when Newton's method is used to solve robust linear regression problems. This leads to easy updates and/or downdates of existing matrix factorizations or easy computation of coefficient matrices in linear systems from previous ones. Thus Newton's method based on these functions has been shown to be computationally cheap. In this paper we show that a combination of Newton's method and an iterative method is a promising approach for solving robust linear regression problems. We show that Newton's method based on the Talwar function is an active set method. Further we show that it is possible to obtain improved estimates of the solution vector by combining a line search method like Newton's method with an active set method.This revised version was published online in October 2005 with corrections to the Cover Date.     

A new method of secant-like for nonlinear equations

In this paper, a new method for solving nonlinear equations f(x) = 0 is presented. In many literatures the derivatives are used, but the new method does not use the derivatives. Like the method of secant, the first derivative is replaced with a finite difference in this new method. The new method converges not only faster than the method of secant but also Newton’s method. The fact that the new method’s convergence order is 2.618 is proved, and numerical results show that the new method is efficient.     

A novel algorithm based on parameterization method for calculation of curvature of the free surface flows

In this paper, a new approach based on parameterization method is presented for calculation of curvature on the free surface flows. In some phenomena such as droplet and bubble, surface tension is prominent. Therefore in these cases, accurate estimation of the curvature is vital. Volume of fluid (VOF) is a surface capturing method for free surface modeling. In this method, free surface curvature is calculated based on gradient of scalar transport parameter which is regarded as original method in this paper. However, calculation of curvature for a circle and other known geometries based on this method is not accurate. For instance, in practice curvature of a circle in interface cells is constant, while this method predicts different curvatures for it. In this research a novel algorithm based on parameterization method for improvement of the curvature calculation is presented. To show the application of parameterization method, two methods are employed. In the first approach denoted by, three line method, a curve is fitted to the free surface so that the distance between curve and linear interface approximation is minimized. In the second approach namely four point method, a curve is fitted to intersect points with grid lines for central and two neighboring cells. These approaches are treated as calculus of variation problems. Then, using the parameterization method, these cases are converted into the sequences of time-varying nonlinear programming problems. With some treatments a conventional equivalent model is obtained. It is finally proved that the solution of these sequences in the models tends to the solution of the calculus of variation problems. For verification of the presented methods, curvature of some geometrical shapes such as circle, elliptic and sinusoidal profile is calculated and compared with original method used in VOF process and analytical solutions. Finally, as a more practical problem, spurious currents are studied. The results showed that more accurate curve prediction is obtained by these approaches than the original method in VOF approach.     

A global convergent quasi-Newton method for systems of monotone equations

In this paper, we propose a quasi-Newton method for solving systems of monotone equations. The method is a combination of the Broyden method and the hyperplane projection method. Under appropriate conditions, we prove that the proposed method is globally convergent. Preliminary numerical results show that the proposed method is promising.     

Convergence analysis of modified Newton-HSS method for solving systems of nonlinear equations

Hermitian and skew-Hermitian splitting(HSS) method has been proved quite successfully in solving large sparse non-Hermitian positive definite systems of linear equations. Recently, by making use of HSS method as inner iteration, Newton-HSS method for solving the systems of nonlinear equations with non-Hermitian positive definite Jacobian matrices has been proposed by Bai and Guo. It has shown that the Newton-HSS method outperforms the Newton-USOR and the Newton-GMRES iteration methods. In this paper, a class of modified Newton-HSS methods for solving large systems of nonlinear equations is discussed. In our method, the modified Newton method with R-order of convergence three at least is used to solve the nonlinear equations, and the HSS method is applied to approximately solve the Newton equations. For this class of inexact Newton methods, local and semilocal convergence theorems are proved under suitable conditions. Moreover, a globally convergent modified Newton-HSS method is introduced and a basic global convergence theorem is proved. Numerical results are given to confirm the effectiveness of our method.     

拟Raabe判别法与拟对数判别法的强弱关系

拟Raabe判别法是新近提出的关于正项级数收敛性的一种比较细致的判别法.对通项递减的正项级数来说,此判别法强于传统的Raabe判别法与Gauss判别法.通过对拟Raabe判别法与另一个细致的判别法——拟对数判别法强弱关系的探讨,得出了后一判别法强于前者的结论.     

Clustering of functional data in a low-dimensional subspace

To find optimal clusters of functional objects in a lower-dimensional subspace of data, a sequential method called tandem analysis, is often used, though such a method is problematic. A new procedure is developed to find optimal clusters of functional objects and also find an optimal subspace for clustering, simultaneously. The method is based on the k-means criterion for functional data and seeks the subspace that is maximally informative about the clustering structure in the data. An efficient alternating least-squares algorithm is described, and the proposed method is extended to a regularized method. Analyses of artificial and real data examples demonstrate that the proposed method gives correct and interpretable results.     

Global convergence of the method of shortest residuals

Summary. The method of shortest residuals (SR) was presented by Hestenes and studied by Pytlak. If the function is quadratic, and if the line search is exact, then the SR method reduces to the linear conjugate gradient method. In this paper, we put forward the formulation of the SR method when the line search is inexact. We prove that, if stepsizes satisfy the strong Wolfe conditions, both the Fletcher-Reeves and Polak-Ribière-Polyak versions of the SR method converge globally. When the Wolfe conditions are used, the two versions are also convergent provided that the stepsizes are uniformly bounded; if the stepsizes are not bounded, an example is constructed to show that they need not converge. Numerical results show that the SR method is a promising alternative of the standard nonlinear conjugate gradient method. Received June 25, 1996 / Revised version received April 1, 1997 / Published online July 28, 1999     

混凝土构件检测样本容量的确定方法

混凝土构件检测时,一般采用百分比抽样的方式.以回弹法中对混凝土强度进行检测时采用百分比抽样的抽样方式为例,从绝对误差限和相对误差限的角度分析了不同构件总量均采用此方法抽取样本的不合理性,并提出在不同混凝土强度等级、不同构件总数的情况下,通过控制一定的误差限来确定样本数量的方法.通过理论和实例分析,提出在抽样过程中,采用分层抽样技术对检测构件进行合理分层,降低总体方差,可减少样本数量.这种方法也适用于其它检测问题的样本容量的确定.     

基于数值分布的激励型综合评价方法

针对激励评价中的等级划分问题,本文提出了一种基于数值分布的等级划分方法,相比于现有的等级划分方法,该方法能够综合考虑数值分布情况来划分等级,并结合本文提出的等级划分法对密度算子进行拓展,提出了一种基于数值分布的激励型综合评价方法。首先本文从数值分布的角度提出了一种新的等级划分方法,从而得出各等级区间的等级区间分界点;其次确定等级系数,并结合指标值和等级区间分界点给出各指标的权向量,给出一种不需要进行归一化处理的等级权向量确定方法,该方法能够较好的解决归一化处理带来的不公平性;再次根据密度算子思想对评价数据进行集结得出评价结果;最后通过一个算例对该方法进行验证,结果表明该方法可以实现对被评价对象科学激励的作用。该方法尤其适用于企业员工激励、省市综合排名、高校人才选拔等问题。