一种新的振荡型DGPM(1,N|sin)模型及其应用

针对传统多变量灰色模型未能有效预测振荡序列的问题,提出一种新的振荡型DGPM(1,N|sin)模型.首先,将非线性时间周期项和时变参数引入离散灰色预测模型;然后,建立非线性规划模型,利用遗传算法确定最优参数;最后,将该模型应用于中国消费价格指数的预测中,验证了本文模型的有效性和适用性.结果显示,振荡型DGPM(1,N|sin)模型有较高的预测精度,为振荡序列的预测提供了有效方法.     

华林问题——三个正立方及一个四次方

设 E(N)为不超过 N 且不能表示为三个正立方及一个四次方之和的正整数个数.本文证明了 E(N)N,这里 s 是任意小的正数.     

基于稳定分布的AR（1）模型的单位根检验

本文考虑误差项为稳定分布的一阶自回归过程Yt =βYt?1+?t (t=1,2,...,N)的单位根检验,其中?t是服从稳定分布的随机误差,β是自回归参数.若β=1成立,则当N →∞时, N (bN ?1)的极限分布可表示为L′evy过程的一个泛函形式,其中bN为β的最小二乘估计.因为该形式不依赖于除特征指数α以外的多余参数,可把N (bN ?1)作为检验原假设H0：β=1的检验统计量. Chan和Tran (1989)通过直接模拟N (bN ?1),给出N (bN ?1)的经验分位数表.但N (bN ?1)的取值与Yt有关,给使用带来影响.本文构造了一个与Yt的取值无关的随机变量EN,n,证明了EN,n与N(bN ?1)有相同的极限分布.通过模拟EN,n,得到N(bN ?1)的经验分位数表.最后,通过三个数值例子说明了方法的有效性.     

Runge-Kutta-Nystr(o)m方法的若干新性质

本文研究了由Runge-Kutta(RK)方法Φ生成Runge-Kutta-Nystr(p)m(RKN)方法ΦN的伴随Φ*N的两种途径,证明了由这两条途径生成的Φ*N是相同的;讨论了具有辛性,对称性或P-稳定性的Φ,ΦN,Φ*N之间的一些关系;并表明通过辛(或对称)RK方法可构造辛(或对称)RKN方法.     

内交换p群的中心扩张(Ⅱ)

设N,H是任意的群.若存在群G,它具有正规子群N≤Z(G),使得N≌N且G/N≌H,则称群G为N被H的中心扩张.本文完全分类了当N为循环p群,H为内交换p群时,N被H的中心扩张得到的所有不同构的群.     

从N!的质因数分解说起——“通解”2019美国数学竞赛AMC10～12

<正>2019美国数学竞赛AMC 10-2题、10-25题(AMC 12-24题)如下:(1)(20!-15!)的百位数是多少?(2)N为整数,1≤N≤50,使得((N~2-1)!/(N!)~N)为整数的N一共有多少个?值得注意的是,这一类含有N!形式的题型经常出现在各种数学竞赛当中.想要"通解"这一类问题,我们先得从质因数分解说起.质因数分解是研究整数规律的一个基本方法.在计算理论和密码学领域,如何快速地分     

对广义Curvature边值问题解的存在性的研究

利用1978年Calvert和Gupta提出的非线性增生映射值域之和的扰动理论,证明了具非线性Neumann边值条件的非线性curvature方程在L~p(Ω)中存在解u(x)的结论,其中(2N)/(N+1)p+∞且N≥1为R~N的维数.文中所研究的方程及所用方法是对以往相关研究工作的推广和补充。为得到文中结论,采用了一些新的证明技巧.     

极大类2群的2次中心扩张

设N,H是任意的群.若存在群G,它有正规子群N≤Z(G),使得N≌N且G/N√≌H,则称群G为N被H的中心扩张.完全分类了当N为2阶循环群及H为极大类2群时,N被H的中心扩张得到的所有互不同构的群.     

Banach空间中算子的秩定理

设E和F是Banach空间,B(E,F)表示映E到F的有界线性算子全体.记T+0 ∈ B(F,E)为T0 ∈ B(E,F)的一个广义逆.本文证明,每一个具有‖T+0(T-T0)‖＜1的算子T ∈ B(E,F),B≡(I+T+0(T-T0))-1T+0是T的广义逆当且仅当(I-T+0T0)N(T)=N(T0),其中N(·)表示括弧中算子的零空间.这一结果改进了Nashed和Cheng的一个有用的定理,并进一步证明Nashed和Cheng的一个引理对半-Fredholm算子有效但一般未必成立.     

亚循环p群的p次中心扩张(Ⅱ)

设N,H是任意的群.若存在群G,它具有正规子群N≤Z(G),使得N≌N且G/N≌H,则称群G为N被H的中心扩张.完全给出了当|N|=2,H为亚循环2群时,N被H的中心扩张得到的所有不同构的群.     

The Convergence of Multigrid Methods for Nonsymmetric Elliptic Variational Inequalities

This paper is concerned with the convergence of multigrid methods (MGM) on nonsymmetric elliptic variational inequalities. On the basis of Wang and Zeng's work (1988), we develop the convergence results of the smoothing operator (i.e. PJOR and PSOR). We also extend the multigrid method of J.Mandel (1984) to nonsymmetric variational inequalities and obtain the convergence of MGM for these problems.     

SINGLE PROJECTION ALGORITHM FOR VARIATIONAL INEQUALITIES IN BANACH SPACES WITH APPLICATION TO CONTACT PROBLEM

We study the single projection algorithm of Tseng for solving a variational inequality problem in a 2-uniformly convex Banach space. The underline cost function of the variational inequality is assumed to be monotone and Lipschitz continuous. A weak convergence result is obtained under reasonable assumptions on the variable step-sizes. We also give the strong convergence result for when the underline cost function is strongly monotone and Lipchitz continuous. For this strong convergence case, the proposed method does not require prior knowledge of the modulus of strong monotonicity and the Lipschitz constant of the cost function as input parameters, rather, the variable step-sizes are diminishing and non-summable. The asymptotic estimate of the convergence rate for the strong convergence case is also given. For completeness, we give another strong convergence result using the idea of Halpern's iteration when the cost function is monotone and Lipschitz continuous and the variable step-sizes are bounded by the inverse of the Lipschitz constant of the cost function.Finally, we give an example of a contact problem where our proposed method can be applied.     

A fixed point method for the linear complementarity problem arising from american option pricing

For American option pricing, the Black-Scholes-Merton model can be discretized as a linear complementarity problem (LCP) by using some finite difference schemes. It is well known that the Projected Successive Over Relaxation (PSOR) has been widely applied to solve the resulted LCP. In this paper, we propose a fixed point iterative method to solve this type of LCPs, where the splitting technique of the matrix is used. We show that the proposed method is globally convergent under mild assumptions. The preliminary numerical results are reported, which demonstrate that the proposed method is more accurate than the PSOR for the problems we tested.     

THE MULTIGRID METHOD OF WILSONELEMENT ON ARBITRARYQUADRILATERAL MESHES WITH TWONEW VARIATIONAL FORMULATIONS

1.IntroductionShiZhongci[']hasshownthattheWilsonelementonarbitraryquadrilateralmesheswasconvergelltunderacertainconditionwithoutmodificationsofthevariationalformulation.P.LesaintandM.Zlamal[2]gaveamathematicalanalysisoftheconvergenceofthemodifiedWilsonelemeflt.Withtheseideas,thispapergivestwosimplevariationalformulationsforthequadrilateralWilsonelementandshowstheirconvergencewiththenewvariationalformulations.Usingthenewvariationalformulations,wecanreduceourcomputationalcostsbecausetwotermsa…     

Progressive Regularization of Variational Inequalities and Decomposition Algorithms

For nonsymmetric operators involved in variational inequalities, the strong monotonicity of their possibly multivalued inverse operators (referred to as the Dunn property) appears to be the weakest requirement to ensure convergence of most iterative algorithms of resolution proposed in the literature. This implies the Lipschitz property, and both properties are equivalent for symmetric operators. For Lipschitz operators, the Dunn property is weaker than strong monotonicity, but is stronger than simple monotonicity. Moreover, it is always enforced by the Moreau–Yosida regularization and it is satisfied by the resolvents of monotone operators. Therefore, algorithms should always be applied to this regularized version or they should use resolvents: in a sense, this is what is achieved in proximal and splitting methods among others. However, the operation of regularization itself or the computation of resolvents may be as complex as solving the original variational inequality. In this paper, the concept of progressive regularization is introduced and a convergent algorithm is proposed for solving variational inequalities involving nonsymmetric monotone operators. Essentially, the idea is to use the auxiliary problem principle to perform the regularization operation and, at the same time, to solve the variational inequality in its approximately regularized version; thus, two iteration processes are performed simultaneously, instead of being nested in each other, yielding a global explicit iterative scheme. Parallel and sequential versions of the algorithm are presented. A simple numerical example demonstrates the behavior of these two versions for the case where previously proposed algorithms fail to converge unless regularization or computation of a resolvent is performed at each iteration. Since the auxiliary problem principle is a general framework to obtain decomposition methods, the results presented here extend the class of problems for which decomposition methods can be used.     

On the modulus algorithm for the linear complementarity problem

Concerning three subclasses of P-matrices the modulus algorithm and the projected successive overrelaxation (PSOR) method solving the linear complementarity problem are compared to each other with respect to convergence. It is shown that the modulus algorithm is convergent for all three subclasses whereas the convergence of the PSOR method is only guaranteed for two of them.     

Simultaneous Subgradient Algorithms for the Generalized Split Variational Inclusion Problem in Hilbert Spaces

In this article, we study the generalized split variational inclusion problem. For this purpose, motivated by the projected Landweber algorithm for the split equality problem, we first present a simultaneous subgradient extragradient algorithm and give related convergence theorems for the proposed algorithm. Next, motivated by the alternating CQ-algorithm for the split equality problem, we propose another simultaneous subgradient extragradient algorithm to study the general split variational inclusion problem. As applications, we consider the split equality problem, split feasibility problem, split variational inclusion problem, and variational inclusion problem in Hilbert spaces.     

Nonlinear uzawa methods for solving nonsymmetric saddle point problems

In [A new nonlinear Uzawa algorithm for generalized saddle point problems, Appl. Math. Comput., 175(2006), 1432–1454], a nonlinear Uzawa algorithm for solving symmetric saddle point problems iteratively, which was defined by two nonlinear approximate inverses, was considered. In this paper, we extend it to the nonsymmetric case. For the nonsymmetric case, its convergence result is deduced. Moreover, we compare the convergence rates of three nonlinear Uzawa methods and show that our method is more efficient than other nonlinear Uzawa methods in some cases. The results of numerical experiments are presented when we apply them to Navier-Stokes equations discretized by mixed finite elements.     

交替方向法求解带线性约束的变分不等式

１引言变分不等式是一个有广泛应用的数学问题,它的一般形式是：确定一个向量,使其满足这里ｆ是一个从到自身的一个映射,Ｓ是Ｒ中的一个闭凸集．在许多实际问题中集合Ｓ往往具有如下结构其中ＡｂＫ是中的一个简单闭凸集．例如一个正卦限,一个框形约束结构,或者一个球简言之,Ｓ是Ｒ中的一个超平面与一个简单闭凸集的交．求解问题（１）－（２）,往往是通过对线性约束Ａ引人Ｌａｇｒａｎｇｅ乘子,将原问题化为如下的变分不等式：确定使得我们记问题（３）－（４）为ＶＩ（Ｆ）．熟知［３］,ＶＩ（,Ｆ）等价于投影方程其中凡（·）表…