解线性互补问题的区间GAOR方法

1引言设M∈Rn×n,q∈Rn,则线性互补问题LCP(M,q)指的是寻找一个向量x∈Rn,使其满足下面的条件: x≥0 Mx+q≥0 xt(Mx+q)=0由于线性互补问题在工程物理、管理学、经济学、约束最优化等领域的应用非常广泛,所以该问题的研究一直倍受大家的关注,至今已有很多有效的算法.早在20世纪80年代     

B-矩阵线性互补问题的误差界估计

正1引言线性互补问题在诸多领域具有广泛的应用,如二次规划、市场均衡、最优停步、双矩阵对策等~([1-3]),线性互补问题的数学模型为求x∈R~n,满足(Mx+q)~Tx=0,Mx+q≥0,x≥0,记作LCP(M,q),其中M=(m_(ij))∈R~(n×n)和q∈R~n为给定的矩阵和向量.线性互补问题解的性质主要取决于所定义矩阵的性质.例如,当矩阵是P-矩阵(即它     

大型对称二次束部分极点配置的多步法

正1引言在结构动力学中,利用有限元技术,对具有n个自由度的阻尼线性系统进行离散化,得到如下的二阶常系数线性微分方程[1]Mx(t)+Cx(t)+Kx(t)=f(t),(1)其中M,C,K∈R~(n×n)分别是对称的质量矩阵、阻尼矩阵和刚度矩阵,且M正定,x(t)∈R~n是位移向量,t表示时间,f(t)是外作用力或控制向量.当f(t)=0时,对(1)进行分离     

一个改进的超记忆梯度法的收敛性及其敛速估计

一、算法 问题:min{f(x)|x∈E~n},f(x)为实值函数; 记号:gj为f(x)在x_j处的梯度列向量,x_*为问题的最优解,H(x)、H_*分别表示f(x)在x和x_*处的Hessian矩阵,上标“,”表示矩阵的转置。 给定实数序列{β_j}、β_j≥0、β_j→0(j→∞),常数a>0,整数k_1相似文献   

向量有理插值的一个行列式公式

<正> 设由不同实数组成的实数序列为x_0,x_1,x_2,…,对应的有限向量序列为(?)_0,(?)_1,(?)_2,…,其中(?)_i=(?)(x_1)∈D~d定义若向量有理函数(?)_n(x)=(?)(x)/q(x),其中(?)(x)是d 维多项式值向量,q(x)是实多项式,满足:     

一类循环和的特性

设φ( x)与ψ( x)均为区间 X上的单调函数 ,对任意 x1、x2 、…、xn ∈ X( n≥ 2 ) ,记Sn( x1,x2 ,… ,xn) =φ ( x1)ψ ( x2 ) φ( x2 )ψ( x3) … φ ( xn-1)ψ ( xn) φ ( xn)ψ( x1) .本文讨论其最值 ,并证明文 [1 ]文 [2 ]的猜想成立 .定理　若 p、q∈ R使一切 x、y、z∈ X满足 S2 ( x,y)≤ p,S3( x,y,z)≤ q,( 1 )则对任意 x1、x2 、…、xn ∈ X　 ( n≥ 2 )有Sn( x1,x2 ,… ,xn)≤ Mn( p,q) ,( 2 )其中Mn( p,q) =12 np,12 ( n - 3) p q,　 n为偶数 ;n为奇数 .证明　 (用数学归纳法 )1°　当 n =2 ,3时 ,由 M2 ( p,q) =p,…     

Cn单位球上的一类Hilbert值函数的收敛性

本文主要研究了Cn单位球上Hilbert值Dμ,q函数的收敛性,得到了若f=∑α≥0xαzα∈Dμ,q,q＞(2n)/(μ),则φ(z)=∑α≥0‖xα‖zα∈Lipγ,其中0＜μ＜1(n=1)或0＜μ＜2(n＞1).此外还得到若f∈Dμ,q,q＞(2n)/(μ),则对几乎所有的{εα}有fω(z)∈H∞,其中0＜μ＜1(n=1)或0＜μ＜2(n＞1).在此过程中,我们利用了Banach空间几何学和Rademacher函数序列的知识.     

Navier-Stokes方程Lq(Rn)弱解的整体存在性

研究不可压Navier-Stokes方程初值在嵋(Rqσ) (q＞n≥2或q=n≥3)上弱解的全局存在性,推广了C.P.Calderon的初值在Lqσ(Rn)(2≤q＜n),n=3,4的结果.作为应用,对任意的k＞0,给定初值f(x)=K(0,-x3/|x|2,x2/|x|2),Naver-Stokes方程都有一个全局弱解.     

偶数阶中立型泛函微分方程最终正解的存在性

获得了偶数阶中立型泛函微分方程[a(t)x(t)-b(t)x(t-r)](n) q(t)f(x(t-σ))=0 (t≥0)存在最终正解的充分条件．     

整数集上四连贯n次多项式的构造

连贯、m (m∈ N,m≥ 3)连贯的定义见[1]或 [2 ].约定 :本文中表示数的字母均表整数 .定理　当an-i =p1 q1 ki-1 (pq1 p1 q) ki pqki 1 ,(i=0 ,1,… ,n- 1,n∈ N,n≥ 2 ,k-1 =k0 =0 )kn =± 1,pq1 - p1 q =± 1,a0 =p1 (q1 kn-1 qkn)时 ,多项式 f (x) =∑n-1i=0an-ixn-i a0 在整数集 Z上连贯 ,且 f(x) j (j =0 ,1)分别有因式px p1 ,qx q1 .证明　这是因为由题设可证得 :f(x) =(px p1 ) ∑n-1i=0(q1 ki qki 1 ) xn-i-1 ,f(x) 1=(qx q1 ) ∑n-1i=0(p1 ki pki 1 ) xn-i-1 .在定理中可选 :(1) kn=1,q1 =rp1 1,p …     

Linearized ridge-path method for function minimization

A modification based on a linearization of a ridge-path optimization method is presented. The linearized ridge-path method is a nongradient, conjugate direction method which converges quadratically in half the number of search directions required for Powell's method of conjugate directions. The ridge-path method and its modification are compared with some basic algorithms, namely, univariate method, steepest descent method, Powell's conjugate direction method, conjugate gradient method, and variable-metric method. The assessment indicates that the ridge-path method, with modifications, could present a promising technique for optimization.This work was in partial fulfillment of the requirements for the MS degree of the first author at Cairo University, Cairo, Egypt. The authors would like to acknowledge the helpful and constructive suggestions of the reviewer.     

A COLUMN-SECANT UPDATE TECHNIQUE FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS

In this paper,we present a column-secant modification of the SCC method,which is called the CSSCC method.The CSSCC method uses function values more efficiently than the SCC method,and it is shown that the CSSCC method has better local q-convergence and r-convergence rates than the SCC method.The numerical results show that the CSSCC method is competitive with some well known methods for some standard test problems.     

一种基于矩阵初等变换的Schmidt正交化方法

对向量组的Schmidt正交化法和合同变换法的关系进行了分析,指出Schmidt正交化法就是合同变换法中利用规范化初等变换后的一种特殊情况,由此给出一种基于矩阵初等变换的Schmidt正交化方法——Schmidt初等变换正交化法,以及这一方法在软件Matlab上实现的程序.     

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.     

A note on estimating parameters in two-parameter Pareto distributions

Pareto distributions are used extensively in modelling income distributions. Estimation of parameters is revisited in two-parameter Pareto distributions. The method of quantile estimates using the elemental estimates and the method of product spacings are applied to the two-parameter Pareto distributions. A comparative study between the maximum likelihood method, the unbiased estimates which are functions of the maximum likelihood method, the minimum mean squared error method, the method of moments, the method of quantile estimation, the method of quantile estimation using the elemental estimates and the method of product spacings is presented.     

用不确定德尔菲法预测GDP

德尔菲法是一种建立在专家意见基础上的预测评估方法.不确定统计是利用不确定理论收集和整理分析专家数据的一种统计方法,其中关键的一点是如何构造不确定变量的不确定分布.把德尔菲法和不确定统计相结合,就得到了一种估计不确定分布的新方法——不确定德尔菲法.对该方法的估计误差进行了改进,得到了一种预测GDP的新方法,并利用其预测邯郸市的生产总值(GDP).     

Iterative Methods of Richardson-Lucy-Type for Image Deblurring

Image deconvolution problems with a symmetric point-spread function arise in many areas of science and engineering. These problems often are solved by the Richardson-Lucy method, a nonlinear iterative method. We first show a convergence result for the Richardson-Lucy method. The proof sheds light on why the method may converge slowly. Subsequently, we describe an iterative active set method that imposes the same constraints on the computed solution as the Richardson-Lucy method. Computed examples show the latter method to yield better restorations than the Richardson-Lucy method and typically require less computational effort.     

自适应多重网格法与超松弛法的比较

多重网格法(Multiple Grid Method,简称M-G方法)是近年来出现的快速方法之一,本文在M-G方法中采用自适应控制层间转换的技术,并将自适应M-G方法与G-S迭代方法及SOR迭代方,法进行了比较。其计算结果表明,自适应M-G方法的计算量比G-S迭代及SOR迭代少得多,当M-G方法所用层数为4-6层,这种优越性就更加明显,且自适应M-G方法中选取控制参数有很大的灵活性。     

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.     

多目标决策问题及其求解方法研究

针对多目标决策问题的多目标最优化问题化为单目标最优化问题进行了研究.其主要方法有:理想点法、等级权重法、加权算术平均法、加权几何平均法、风险偏好系数法、乘除法、模糊规划法等.此外,还对多目标最大最小和多目标最小最大决策问题进行了处理.