反自反的

In this paper, we deal with the complete extension of a fuzzy relation and obtain the following main conclusion. Every reflexive,*-antisymmetric and *-transitive fuzzy relation can be extended to a complete reflexive,*-antisymmetric and *-transitive fuzzy relation, namely, every partial order can be extended to a linear order.

文章研究了一个模糊关系的完全扩张问题，主要结果为：一个自反的、*-反对称的*、-传递的模糊关系可以扩张成为一个完全的、自反的、*-反对称的、*-传递的模糊关系，即任何一个偏序都可以扩张成一个线性序。

It is difficult to judge a transitive binary-relation by using the definition of transitivity of binary relation directly.

0引言定义在某一集合上的二元关系具有自反性、反自反性、对称性、反对称性以及传递性等性质。

Exive least-squares solutions, antire?exive least-squares solutions, bisymmetric least-squaressolutions, symmetric and antipersymmetric least-squares solutions, symmetric or-thogonal symmetric least-squares solutions, symmetric orthogonal antisymmetricleast-squares solutions and their optimal approximation to the linear matrix equa-tion AX = B, and solve them successfully. 2. For Problem II, we can convert it to another problem of finding the least-squares solutions with the least norm of a new consistent matrix equation. Onthe base of the solutions of Problem I we can apply the iterative method to get

本文所构造的迭代法的优点在于先利用法方程变换将求矩阵方程的最小二乘解转化为求一个相容矩阵方程的解的问题，再利用迭代法对于任意给定的初始矩阵进行迭代，均可在有限步内迭代出所求问题的一个解；可将问题II转化为求新方程的极小范数解的问题，同样用迭代法求解，从而系统且全面地解决了问题I、II在约束矩阵类如中心对称、中心反对称、自反矩阵、反自反矩阵、双对称、对称次反对称、对称正交对称、对称正交反对称矩阵中的最小二乘解及其最佳逼近问题。

This thesis focuses on studying the matrix equa-tion problem systematically, and proposed an abstract algorithm of solving the matrixequation with constraints, and established a strict convergence theory. Using this algo-rithm, we can solve the sets of matrix equation satisfying some constraint conditions,such as symmetric, antisymmetric, centrosymmetric, centroskew symmetric, re?exive,antire?exive, bisymmetric, symmetric and antipersymmetric, symmetric orthogonalsymmetric, symmetric orthogonal antisymmetric, Hermite generalized Hamilton ma-trix;So we can solve the problem with this algorithm, if the set of constrain matrixcan make a subspace in matrix space, and this algorithm also can solve the optimalapproximation and least squares problem. So this abstract algorithm has universal andimportant practical value.

本篇硕士论文系统地研究了此类问题，并找到了求解约束矩阵问题的抽象算法，并建立严格的收敛性理论，利用这一算法可求解约束条件为对称矩阵、反对称矩阵、中心对称矩阵、中心反对称矩阵、自反矩阵、反自反矩阵，对称正交对称矩阵、对称正交反对称矩阵、双中心矩阵、Hermite广义Hamilton矩阵等；可以说只要约束矩阵集合在矩阵空间中构成子空间，都可以考虑用此算法求解，而且这一算法还能把矩阵方程解及其最佳逼近，最小二乘解及其最佳逼近统一处理，因此本文算法有普适性和重要的实用价值。

The solutions of ProblemⅠ,ⅡandⅢare discussed by using the generalized conjugate gradient method. When the equation is consistent, the solutions such as symmetric, skew-symmetric, centrosymmetric, centroskew symmetric, reflexive, antireflexive, bisymmetric or symmetric and antipersymmetric are successfully found; When the equation is inconsistent, the least-squares solutions such as symmetric, skew-symmetric, centrosymmetric, centroskew symmetric, reflexive, antireflexive, bisymmetric or symmetric and antipersymmetric are also found successfully. The generalized conjugate gradient method has the following traits:(1) It can judge automatically the information of solutions.

利用广义共轭梯度法，讨论了问题Ⅰ、Ⅱ和Ⅲ解的情况：当方程相容时，研究了方程的一般解、对称解、中心对称解、自反矩阵解、双对称解、对称次反对称解及其最佳逼近等问题；当方程不相容时，研究了方程的最小二乘一般解、最小二乘对称解、最小二乘中心对称解、最小二乘自反矩阵解、最小二乘双对称解、最小二乘对称次反对称解及其最佳逼近等问题。

Problem III Given find such thatProblem IV When Problem I or II or III is consistent, let Se denote the set of its solutions, for given , find , such thatwhere is Frobenius norm, S is Rn×p or a subset of Rn×p satisfying some constraint conditions, such as symmetric, skew-symmetric, centrosymmet-ric, centroskew symmetric, reflexive, antireflexive, bisymmetric or symmetric and antipersymmetric.

问题Ⅳ 设问题Ⅰ或Ⅱ或Ⅲ相容，且其解集合为SE，给定X0∈Rn×p，求X∈SE，使其中‖·‖为Frobenius范数，S为Rn×p或为Rn×p中满足某约束条件的矩阵集合，如对称矩阵、反对称矩阵、中心对称矩阵、中心反对称矩阵、自反矩阵、反自反矩阵、双对称矩阵、对称次反对称矩阵等。

R~, find∈S_E, such that ProblemⅤGiven, find [X_1,X_2,…,X_l](where X_i∈S_i,i=1,2,…,l), such that A_1X_1B_1+A_2X_2B_2+…+A_lX_lB_l=C ProblemⅥWhen ProblemⅤis consistent, let SE denote the set of its solutions, for given,find, such that where||·|| is Frobenius norm, S and S_i are the matrix set satisfying some constraint conditions such as symmetric, skew-symmetric, centrosymmetric, centroskew symmetric, reflexive, antireflexive, bisymmetric or symmetric and antipersymmetric.

R~，求∈S_E，使得问题Ⅴ给定，求[X_1，X_2，…，X_l](其中X_i∈S_i，i=1，2，…，l)，使得 A_1X_1B_1+A_2X_2B_2+…+A_lX_lB_l=C 问题Ⅵ设问题Ⅴ相容，且其解集合为S_E，给定矩阵组，求，使得其中||·||为Frobenius范数，S，S_i为满足某种约束条件的矩阵集合，如对称矩阵、反对称矩阵、中心对称矩阵、中心反对称矩阵、自反矩阵、反自反矩阵、双对称矩阵、对称次反对称矩阵等等。

Based on English definition of the six properties which a relation R defined on a set A and utilizing the logical characteristic of implications, two aspects of ordered-pair and the matrix MR are considered, and the properties of the R is analyzed one by one. A few useful conclusions are summarized as determining the properey of the R. The following collections are also analyzed between reflexive and irreflexive, symmetric and antisymmetric, symmetric and asymmetric and among irreflexive, antisymmetric and asymmetric.

根据定义在一个集合A上的关系R的六个性质的英文定义，利用蕴含式的逻辑特点，从有序对和关系R的矩阵M两个角度对每个性质逐一进行分析，得出在判定关系R的性质时可用的结论，并且分析了自反性与非自反性之间、对称性与反对称性之间、对称性与非对称性之间、非自反性和反对称性以及非对称性之间的联系。

Denotes the Frobenius norm, S is a subset of Rn×n. This master thesishas mainly studied centrosymmetric matrix set, centroskew symmetric matrix set,re?

为Frobenius范数， S为Rn×n中满足某约束条件的矩阵集合，本硕士论文主要研究了中心对称矩阵、中心反对称矩阵、自反矩阵、反自反矩阵、双对称矩阵、对称次反对称矩阵、对称正交对称矩阵、对称正交反对称矩阵。

For problem II, many references have studied it and obtained its common solutions, symmetric solutions, skew-symmetric solutions and its optimal approximation constrained solution, but the representation of its solutions are complicated.

本文首次采用迭代法系统的研究了它求一般解、对称解、反求解约束矩阵方程及其最佳逼近的迭代法的研究对称解、中心对称解、中心反对称解、自反矩阵解、反自反矩阵解、双对称解、对称次反对称解及其最佳逼近问题，并首次成功地解决了它求中心对称解、中心反对称解、自反矩阵解、反自反矩阵解、双对称解与对称次反对称解及其最佳逼近的问题，拓广和改进了已有的研究成果。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。