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Selfconjugate matrix, skewselfconjugate matrix, perselfconjugate matrix, skewperselfconjugate matrix, centrosymmetric matrix, skewcentrosymmetric matrix, bisymmetric matrix, and skewbisymmetric matrix over a ring with an involutorial antiautomorphism are defined. Significant criteria for matrices to be bisymmetric and skewbisymmetric are obtained.

在具有对合反自同构的环上定义了自共轭矩阵,斜自共轭矩阵,广自共轭矩阵,斜广自共轭矩阵,中心对称矩阵,斜中心对称矩阵,双对称矩阵和斜双对称矩阵,建立了双对称矩阵和斜双对称矩阵的重要判定定理。

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。

By using constructive methods and complicated techniques of matrices, necessary and sufficient conditions for the existence of selfconjugate solution, perselfconjugate solution, centrosymmetric solution, bisymmetric solution, skewselfconjugate solution, skewperselfconjugate solution, skewcentrosymmetric solution, skewbisymmetric solution and various interlaced solutions over a finite central algebra Ω to systems of generalized Sylvester matrix equations overΩ are presented.

利用构造方法和复杂的矩阵技巧,研究了有限维中心代数上的多项式环Ω上的广义Sylvester矩阵方程组在Ω上有自共轭解,斜自共轭解,广自共轭解,斜广自共轭解,中心对称解,斜中心对称解,双对称解,斜双对称解及其各种交错解的充要条件。

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。

The concepts in References 1 and 2 are broadened and the properties of the centrosymmetric and skew centrosymmetric matrices are exploited in detail.

推广了文[1,2]的概念,系统地叙述了中心对称和反中心对称矩阵的性质,导出了一类求解系数矩阵为中心对称和反中心对称线性方程组及超定方程组的缩减算法。

By this iterative method ,the solvability of the matrix equation can be judged automatically.When the matrix equation is consistent ,then,for any initial centrosymmetric matrix pair ,a centrosymmetric solution pair can be obtained within finite iteration steps in the absence of roundoff errors, and the least norm centrosymmetric solution pair can be obtained by choosing a special kind of initial centrosymmetric matrix pair.

当矩阵方程相容时,对任意初始的中心对称矩阵对在没有舍入误差的情况下,经过有限步迭代,得到它的一个中心对称解,并且,通过选择一种特殊的中心对称矩阵对,得到它的最小范数中心对称解。

When the matrix equation is consistent, its centrosymmetric solution can be obtained within finite iterative steps in the absence of round off errors for any initial centrosymmetric matrix X1, and its least-norm centrosymmetric solution can be derived by choosing a suitable initial iterative matrix.

当矩阵方程AXB+CXD=F有中心对称解时,在有限的误差范围内,对任意初始中心对称矩阵X1,运用迭代算法,经过有限步可得到矩阵方程的中心对称解;选取合适的初始迭代矩阵,还可以迭代出极小范数中心对称解。

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。

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