MULTILEVEL AUGMENTATION METHODS FOR SOLVING OPERATOR EQUATIONS

We introduce multilevel augmentation methods for solving operator equations based on direct sum decompositions of the range space of the operator and the solution space of the operator equation and a matrix splitting scheme. We establish a general setting for the analysis of these methods, showing that the methods yield approximate solutions of the same convergence order as the best approximation from the subspace. These augmentation methods allow us to develop fast, accurate and stable nonconventional numerical algorithms for solving operator equations. In particular, for second kind equations, special splitting techniques are proposed to develop such algorithms. These algorithms are then applied to solve the linear systems resulting from matrix compression schemes using wavelet-like functions for solving Fredholm integral equations of the second kind. For this special case, a complete analysis for computational complexity and convergence order is presented. Numerical examples are included to demonstra     

Algorithms for Finding the Inverses of Factor Block Circulant Matrices

In this paper,algorithms for finding the inverse of a factor block circulant matrix, a factor block retrocirculant matrix and partitioned matrix with factor block circulant blocks over the complex field are presented respectively.In addition,two algorithms for the inverse of a factor block circulant matrix over the quaternion division algebra are proposed.     

The State Equations Methods for Stochastic Control Problems

<正>The state equations of stochastic control problems,which are controlled stochastic differential equations,are proposed to be discretized by the weak midpoint rule and predictor-corrector methods for the Markov chain approximation approach. Local consistency of the methods are proved.Numerical tests on a simplified Merton's portfolio model show better simulation to feedback control rules by these two methods, as compared with the weak Euler-Maruyama discretisation used by Krawczyk.This suggests a new approach of improving accuracy of approximating Markov chains for stochastic control problems.     

一类奇性积分方程的多尺度配置快速算法

This paper develops fast multiscale collocation methods for a class of Fredholm integral equations of the second kind with singular kernels. A truncation strategy for the coefficient matrix of the corresponding discrete system is proposed, which forms a basis for fast algorithms. The convergence, stability and computational complexity of these algorithms are analyzed.     

ON SOLUTIONS OF QUATERNION MATRIX EQUATIONS XF-AX=BY AND XF-A=BY

In this paper,the quaternion matrix equations XF-AX=BY and XF-A=BY are investigated.For convenience,they were called generalized Sylvesterquaternion matrix equation and generalized Sylvester-j-conjugate quaternion matrix equation,which include the Sylvester matrix equation and Lyapunov matrix equation as special cases.By applying of Kronecker map and complex representation of a quaternion matrix,the sufficient conditions to compute the solution can be given and the expressions of the explicit solutions to the above two quaternion matrix equations XF-AX=BY and XF-A=BY are also obtained.By the established expressions,it is easy to compute the solution of the quaternion matrix equation in the above two forms.In addition,two practical algorithms for these two quaternion matrix equations are give.One is complex representation matrix method and the other is a direct algorithm by the given expression.Furthermore,two illustrative examples are proposed to show the efficiency of the given method.     

QR factorization for row or column symmetric matrix

The problem of fast computing the QR factorization of row or column symmetric matrix is considered. We address two new algorithms based on a correspondence of Q and R matrices between the row or column symmetric matrix and its mother matrix. Theoretical analysis and numerical evidence show that, for a class of row or column symmetric matrices, the QR factorization using the mother matrix rather than the row or column symmetric matrix per se can save dramatically the CPU time and memory without loss of any numerical precision.     

Convergence and complexity of arbitrary order adaptive mixed element methods for the Poisson equation

This paper discusses convergence and complexity of arbitrary,but fixed,order adaptive mixed element methods for the Poisson equation in two and three dimensions.The two main ingredients in the analysis,namely the quasi-orthogonality and the discrete reliability,are achieved by use of a discrete Helmholtz decomposition and a discrete inf-sup condition.The adaptive algorithms are shown to be contractive for the sum of the error of flux in L2-norm and the scaled error estimator after each step of mesh refinement and to be quasi-optimal with respect to the number of elements of underlying partitions.The methods do not require a separate treatment for the data oscillation.     

PROXIMAL POINT ALGORITHM FOR MINIMIZATION OF DC FUNCTION

In this paper we present some algorithms for minimization of DC function (difference of two convex functions). They are descent methods of the proximal-type which use the convex properties of the two convex functions separately. We also consider an approximate proximal point algorithm. Some properties of the ε-subdifferentiM and the ε-directional derivative are discussed. The convergence properties of the algorithms are established in both exact and approximate forms. Finally, we give some applications to the concave programming and maximum eigenvalue problems.     

MATRIX ALGORITHMS AND ERROR FORMULA FOR BIVARIATE THIELE-TYPE RECTANGULAR MATRIX VALUED RATIONAL INTERPOLATION

A new method for the construction of bivariate matrix valued rational interpolants (BGIRI) on a rectangular grid is presented in [6]. The rational interpolants are of Thiele-type continued fraction form with scalar denominator. The generalized inverse introduced by [3]is gen-eralized to rectangular matrix case in this paper. An exact error formula for interpolation is ob-tained, which is an extension in matrix form of bivariate scalar and vector valued rational interpola-tion discussed by Siemaszko[l2] and by Gu Chuangqing [7] respectively. By defining row and col-umn-transformation in the sense of the partial inverted differences for matrices, two type matrix algorithms are established to construct corresponding two different BGIRI, which hold for the vec-tor case and the scalar case.     

Primal-dual Interior-point Algorithms for Second-order Cone Optimization Based on a New Parametric Kernel Function

A class of polynomial primal-dual interior-point algorithms for second-order cone optimization based on a new parametric kernel function, with parameters p and q, is presented. Its growth term is between linear and quadratic. Some new tools for the analysis of the algorithms are proposed. The complexity bounds of O（√Nlog N log N/ε） for large-update methods and O（√Nlog N/ε） for smallupdate methods match the best known complexity bounds obtained for these methods. Numerical tests demonstrate the behavior of the algorithms for different results of the parameters p and q.     

六类不确定型判断矩阵的相容性研究

介绍区间数互补判断矩阵、区间数互反判断矩阵、区间数混合判断矩阵、三角模糊数互补判断矩阵、三角模糊数互反判断矩阵和三角模糊数混合判断矩阵等概念，给出衡量六类不确定型判断矩阵(区间数互补判断矩阵、区间数互反判断矩阵、区间数混合判断矩阵、三角模糊数互补判断矩阵、三角模糊数互反判断矩阵以及三角模糊数混合判断矩阵)同类型之间相容性的两个通用指标，并给出上述六类不确定型判断矩阵相容性的度量准则，最后进行算例分析。     

两类区间数判断矩阵的一致性研究

研究了区间数互反判断矩阵和区间数互补判断矩阵一致性的关系，并讨论了一致性区间数互补判断矩阵的性质，给出了一种区间数互补判断矩阵一致性的判定方法。     

基于相容性的模糊判断矩阵一致性改进新方法

模糊判断矩阵是决策者给出的一种重要的偏好信息形式。根据模糊判断矩阵互补性的特点,提出一个模糊判断矩阵相容性的指标,并研究模糊判断矩阵相容性和一致性的关系,在此基础上定义了一个模糊判断矩阵与其特征矩阵的偏差矩阵,给出了一致性改进的新方法,最后进行了实例分析,结果表明该方法行之有效。     

区间数互补判断矩阵的一种新排序算法

针对区间数互补判断矩阵元素表示的特点,定义了区间数互补判断矩阵的等价矩阵族,得到了区间数互补矩阵一致性检验方法.通过构造一种新的求解区间数互补判断矩阵的权重区间的决策模型,得到一种排序算法.最后给出一个算例,描述此方法的应用.     

互补判断矩阵排序的最小偏差法的性质

互补判断矩阵是决策给出的一种重要的偏好信息形式。本基于完全一致性互补判断矩阵的定义。提出互补判断矩阵排序的最小偏差法，研究了它的一些优良性质，包括强条件下保序性、置换不变性、相容性等，最后给出了一个算例，结果表明该种排序方法是有效的。     

群组决策的综合判断矩阵及一致性调整

对群组决策的综合判断矩阵的一致性进行了研究 ,给出了一种确定群组决策的综合判断矩阵并对它进行一致性调整的算法 .     

模糊判断矩阵一致性的调整方法

给出了模糊判断矩阵一致性调整的新方法 .该方法是在模糊判断矩阵一致性定义及判定方法的基础上 ,通过构造和分析模糊判断矩阵的调和矩阵 ,进一步给出了将模糊判断矩阵改进为满意一致性矩阵的计算步骤 .最后给出了一个算例 .     

一种校正模糊判断矩阵一致性的新方法

给出一种校正模糊判断矩阵一致性的新方法。首先 ,给出关于模糊判断矩阵满意一致性的定义及判定方法 ,然后通过构造和分析能够反映完全一致性矩阵和原判断矩阵之间关系的偏差矩阵 ,给出校正模糊判断矩阵一致性的计算步骤 ,最后给出了一个算例。     

模糊判断矩阵的相容性研究

模糊判断矩阵是决策在决策中所提供的一种重要的偏好信息。根据模糊判断矩阵互补性的特点，提出一个相容性的新指标，该指标简单易算，并研究模糊判断矩阵相容性和一致性的关系，给出了满意相容性的一个准则，最后进行了实例分析，结果令人满意。     

模糊互补判断矩阵一致性改进的新途径

针对模糊互补判断矩阵的一致性修正问题,本文从模糊一致矩阵传统定义出发,深入挖掘了一致性定义中所涉及到的三元素组之间的关系,在给出相关定理的基础上,提出了一种改善模糊互补判断矩阵一致性的新算法,从理论上分析了该算法的可行性,并利用模拟仿真的方法给出了与本算法相关的几种比较分析。