球面带形平移网络逼近的Jackson定理

研究了球面带型平移网络逼近阶用球面调和多项式的最佳逼近及光滑模的刻画问题．借助于球调和多项式的最佳逼近多项式和Riesz平均构造出了单位球面Sq上的带形平移网络,并建立了球面带形平移网络对Lp(Sq)中函数一致逼近的Jackson型定理．所得结果表明球面带形平移网络可以达到球调和多项式的逼近阶．     

Orlicz空间中Kantorovi算子逼近等价定理

以带权函数的连续模为工具 ,讨论了 Kantorovic算子在 Orlicz空间中逼近的正、逆定理 ,进而得到其等价刻划 .     

Orlicz空间中Kantorovi(c)算子逼近等价定理

以带权函数的连续模为工具,讨论了Ｋａｎｔｏｒｏｖｉｃ算子在Ｏｒｌｉｃｚ空间中逼近的正、逆定理,进而得到其等价刻划。     

多元推广的Bernstein算子的逼近性质

构造了一类一致收敛于被逼近函数的多元序列,以此序列为基础,运用多元函数的全连续模及部分连续模来刻画这种多元推广的Bernstein算子的逼近性质,不仅得出了理论逼近结果,而且给出了数值逼近的例子.     

Baskakov算子线性组合加权同时逼近的正定理

在加Jacobi权函数w(t)下,利用光滑模ω_(φλ)~r(f,t)_w与带权K-泛函的等价关系,研究了Baskakov算子线性组合对空间C[0,∞]中函数的逼近性质,并给出了其加权同时逼近的正定理,完善了以前的相应结论.     

Bernstein型多项式逼近的逆定理

对于Bernstein型多项式，利用强Voronovskaja型展开，证明该多项式逼近连续函数强型逆定理，从而用Ditzian-Totik模刻画该多项式逼近阶的特征，得到了等价刻画定理．     

Shepard-Lagrange算子的逼近

本文建立了Shepard-Lagrange算子逼近的正逆定理,证明了可以利用高阶光滑模来刻画Shepard-Lagrange算子的逼近性质.从而说明了Shepard-Lagrange算子比一般的Shepard算子具有更好的逼近性质.进一步,所用光滑模的阶梯函数非常广泛,这是多项式逼近所不具有的.     

带Hilbert核奇异积分方程的Galerkin方法

该文讨论了以下形式的奇异积分方程其中ａ（ｘ），ｂ（ｘ），ｆ（ｘ），（ｘ）∈Ｈ（２π），ｋ（ｘ，ｔ）关于ｘ，ｔ也∈Ｈ（２π）的数值解法．在Ｌ２模下，得出了逼近解的存在性和收敛性；当ｆ（Ｘ），ｋ（ｘ，ｔ）∈Ｈμ２π，μ＞时，逼近解在最大模下一致收敛到精确解；当ｆ（ｐ）（Ｘ），ｋ（ｘ，ｔ）∈Ｈμ２π时，逼近解对精确解的逼近阶．     

某些广义插值在L^2πp和Lp（R）空间的逼近

给出了两种插值算子，并研究了它们在L^2πp和Lp(R)空间上的逼近阶，用实数α阶的积分模给出逼近度。     

带弱奇异核非线性积分微分方程的有限元分析

讨论了带弱奇异核的非线性抛物积分微分方程的Hermite型各向异性矩形元逼近.在各向异性网格下导出了关于Riesz投影的L~2和H~1模的误差估计.在半离散和向后欧拉全离散格式下,基于Riesz投影的性质并利用平均值技巧,分别得到了L~2模意义下的最优误差估计.     

Minimum norm solutions for cooperative games

A solution f for cooperative games is a minimum norm solution, if the space of games has a norm such that f(v) minimizes the distance (induced by the norm) between the game v and the set of additive games. We show that each linear solution having the inessential game property is a minimum norm solution. Conversely, if the space of games has a norm, then the minimum norm solution w.r.t. this norm is linear and has the inessential game property. Both claims remain valid also if solutions are required to be efficient. A minimum norm solution, the least square solution, is given an axiomatic characterization.      

关于最小二乘QR分解算法(LSQR)的一个注记

本文从最小多项式出发,通过寻找包含奇异线性系统Ax=b最小范数解的一个解空间,获得了一个更简单的求解广义逆的计算公式.并从理论上对最小二乘QR分解算法（LSQR）收敛性进行了简单分析,分析表明LSQR的收敛性与矩阵A的非零奇异值密切相关,并用A的非零奇异值以及所寻找到的最小范数解空间将最小范数解线性表出.     

Discrete ill-posed least-squares problems with a solution norm constraint

Straightforward solution of discrete ill-posed least-squares problems with error-contaminated data does not, in general, give meaningful results, because propagated error destroys the computed solution. Error propagation can be reduced by imposing constraints on the computed solution. A commonly used constraint is the discrepancy principle, which bounds the norm of the computed solution when applied in conjunction with Tikhonov regularization. Another approach, which recently has received considerable attention, is to explicitly impose a constraint on the norm of the computed solution. For instance, the computed solution may be required to have the same Euclidean norm as the unknown solution of the error-free least-squares problem. We compare these approaches and discuss numerical methods for their implementation, among them a new implementation of the Arnoldi–Tikhonov method. Also solution methods which use both the discrepancy principle and a solution norm constraint are considered.     

A Concentration Theorem for the Heat Equation

 We compare the solution of to the solution of the same equation where f is replaced by a “concentrated” source . As a result we derive some estimates on the solution in spatial norm, locally uniformly in t, with respect to the norm of for any integer . In the case we obtain a critical inequality relating the norm of to an exponential norm of u. (Received 1 September 2000; in revised form 17 January 2001)     

Numerical treatment of integro-differential equations with a certain maximum property

The purpose of this article is to study the solution of an initial value problem of integro-differential type, where the differentiation is made for the timevariable and the integration for the space-variable. The problem has a propertyC, which implies that the solution is decreasing at the maximum-points. It is shown, that under rather general conditions, the solution tends to a constant, independent of both time and space. In the proofs, use is made of both the maximum norm and a weighted Euclidean norm.In order to study the numerical solution the problem is first discretized in the space-variable, preserving the propertyC. Finally, the problem is solved as a system of ordinary differential equations, making use of the propertyC to obtain not too pessimistic error estimations. The logarithmic norm, based on the maximum norm, is very useful in these final sections.     

Sylvester矩阵方程极小范数最小二乘解的迭代解法

研究了Sylvester矩阵方程最小二乘解以及极小范数最小二乘解的迭代解法,首先利用递阶辨识原理,得到了求解矩阵方程AX+YB=C的极小范数最小二乘解的一种迭代算法,进而,将这种算法推广到一般线性矩阵方程A_iX_iB_i=C的情形,最后,数值例子验证了算法的有效性.     

On the uniqueness of solutions to the Poisson equations for average cost Markov chains with unbounded cost functions

We consider the Poisson equations for denumerable Markov chains with unbounded cost functions. Solutions to the Poisson equations exist in the Banach space of bounded real-valued functions with respect to a weighted supremum norm such that the Markov chain is geometrically ergodic. Under minor additional assumptions the solution is also unique. We give a novel probabilistic proof of this fact using relations between ergodicity and recurrence. The expressions involved in the Poisson equations have many solutions in general. However, the solution that has a finite norm with respect to the weighted supremum norm is the unique solution to the Poisson equations. We illustrate how to determine this solution by considering three queueing examples: a multi-server queue, two independent single server queues, and a priority queue with dependence between the queues.     

求矩阵方程组的反对称最小二乘解的递推算法

讨论了矩阵方程组A_1XB_1=D_1,A_2XB_2=D_2反对称最小二乘解的递推算法,该算法不仅能够用于计算反对称最小二乘解,而且在选取特殊的初始矩阵时,算法能够求出矩阵方程组的极小范数反对称最小二乘解,以及对给定的矩阵进行最佳逼近的反对称解.     

Method for finding an approximate solution of the asphericity problem for a convex body

Given a convex body, the finite-dimensional problem is considered of minimizing the ratio of its circumradius to its inradius (in an arbitrary norm) by choosing a common center of the circumscribed and inscribed balls. An approach is described for obtaining an approximate solution of the problem, whose accuracy depends on the error of a preliminary polyhedral approximation of the convex body and the unit ball of the used norm. The main result consists of developing and justifying a method for finding an approximate solution with every step involving the construction of supporting hyperplanes of the convex body and the unit ball of the used norm at some marginal points and the solution of a linear programming problem.     

Stability of best approximation of a convex body by a ball of fixed radius

The finite-dimensional problem of the best approximation (in the Hausdorff metric) of a convex body by a ball of arbitrary norm with a fixed radius is considered. The stability and sensitivity of the solution to errors in specifying the convex body to be approximated and the unit ball of the used norm are analyzed. It is shown that the solution of the problem is stable with respect to the functional and, if the solution is unique, the center of the best approximation ball is stable as well. The sensitivity of the solution to the error with respect to the functional is estimated (regardless of the radius of the ball). A sensitivity estimate for the center of the best approximation ball is obtained under the additional assumption that the estimated body and the ball of the used norm are strongly convex. This estimate is related to the range of radii of the approximating ball.