矩阵方程AX=B,XC=D的定秩解

本文研究了一类矩阵方程组解的秩的范围.利用矩阵的奇异值分解以及Frobenius范数的特征,得到了解的极值秩以及解的通式,并就这些问题的特殊情况进行了讨论,得到了一些结果.     

Optimal Control of Linear Time-Varying Systems via Haar Wavelets

This paper introduces the application of Haar wavelets to the optimal control synthesis for linear time-varying systems. Based upon some useful properties of Haar wavelets, a special product matrix, a related coefficient matrix, and an operational matrix of backward integration are proposed to solve the adjoint equation of optimization. The results obtained by the proposed Haar approach are almost the same as those obtained by the conventional Riccati method.     

矩阵方程AXA^T＋BYB^T=C的双对称最小二乘解及其最佳逼近

基于共轭梯度法的思想,通过特殊的变形,建立了一类求矩阵方程AXA^T＋BYB^T=C的双对称最小二乘解的迭代算法．对任意的初始双对称矩阵．在没有舍人误差的情况下,经过有限步迭代得到它的双对称最小二乘解;在选取特殊的初始双对称矩阵时,能得到它的的极小范数双对称最小二乘解．另外,给定任意矩阵,利用此方法可得到它的最佳逼近双对称解,数值例子表明,这种方法是有效的．     

相容次序矩阵PSD迭代法的收敛性

本文是在求解大型线性方程组Ax=b的系数矩阵A为(1,1)相容次序矩阵且其Jacobi迭代矩阵的特征值均为纯虚数或零的条件下,得到PSD迭代法收敛的充分必要性定理,并在特殊情况下得到了相应的最优参数.     

求矩阵方程AXB+CXD=F的中心对称最小二乘解的迭代算法

该文建立了求矩阵方程AXB+CXD=F的中心对称最小二乘解的迭代算法.使用该算法不仅可以判断该矩阵方程的中心对称解的存在性,而且无论中心对称解是否存在,都能够在有限步迭代计算之后得到中心对称最小二乘解.选取特殊的初始矩阵时,可求得极小范数中心对称最小二乘解.同时,也能给出指定矩阵的最佳逼近中心对称矩阵.     

A-Parseval框架小波的特征刻画

研究与伸缩矩阵A相关的Parseval框架小波(A-PFW)的特征刻画,其中伸缩矩阵A满足A~3=2I_3且A的每一列元素之和均为偶数.首先,讨论了与两个特殊伸缩矩阵B,C相关的Parseval框架小波(B-PFW,C-PFW)之间的关系,并得到C-PFW分别与两类特殊伸缩矩阵D,■相关的Parseval框架小波(D-PFW,■-PFW)之间的等价关系.其次,探讨了伪尺度函数和源于多分辨分析的A-PFW(MRA A-PFW)的特征刻画.最后,借助于维数函数,给出了A-PFW是MRA A-PFW的一个充要条件.     

Reproducing Kernel for D2(Ω, ρ) and Metric Induced by Reproducing Kernel

An important property of the reproducing kernel of D2(Ω, ρ) is obtained and the reproducing kernels for D2(Ω, ρ) are calculated when Ω = Bn × Bn and ρ are some special functions. A reproducing kernel is used to construct a semi-positive definite matrix and a distance function defined on Ω×Ω. An inequality is obtained about the distance function and the pseudodistance induced by the matrix.     

线性泛函微分方程关于部分变元稳定性的充要条件

本文在引进具有界滞量线性泛函微分方程的Cauchy矩阵的截断矩阵与截断解算子概念的基础上 ,讨论了这类方程关于部分变元各种稳定性的充要条件 .本文包含此类方程相应的关于全体变元稳定性的经典结论为其特例 .     

The distribution of a generalized least squares estimator with covariance adjustment

The distribution theory is developed for a generalized least squares estimator of the growth curve model. A special case of the estimator is the maximum likelihood estimator which is weighted by the sample covariance matrix. The distribution of two conditional forms of the estimator are derived and from these its density is obtained. Two general pivots and their distributions are derived from the conditional forms and special cases of these are investigated. The results obtained are linked to carlier work.     

Finite iterative method for solving coupled Sylvester-transpose matrix equations

This paper is concerned with solutions to the so-called coupled Sylvester-transpose matrix equations, which include the generalized Sylvester matrix equation and Lyapunov matrix equation as special cases. By extending the idea of conjugate gradient method, an iterative algorithm is constructed to solve this kind of coupled matrix equations. When the considered matrix equations are consistent, for any initial matrix group, a solution group can be obtained within finite iteration steps in the absence of roundoff errors. The least Frobenius norm solution group of the coupled Sylvester-transpose matrix equations can be derived when a suitable initial matrix group is chosen. By applying the proposed algorithm, the optimal approximation solution group to a given matrix group can be obtained by finding the least Frobenius norm solution group of new general coupled matrix equations. Finally, a numerical example is given to illustrate that the algorithm is effective.     

Szegö-Kac-Achiezer formulas in terms of realizations of the symbol

For rational and analytic matrix functions new formulas are obtained for the limits in the Szegö-Kac-Achiezer limit theorems. In the rational case the new expressions are given in terms of finite matrices which come from special representations of the matrix functions. These representations are known as realizations in mathematical systems theory.     

$D^2(\Omega,\rho)$的再生核与再生核诱导的度量

An important property of the reproducing kernel of D^2（Ω, ρ） is obtained and the reproducing kernels for D^2（Ω, ρ） are calculated when Ω = Bn× Bn and ρ are some special functions. A reproducing kernel is used to construct a semi-positive definite matrix and a distance function defined on Ω×Ω. An inequality is obtained about the distance function and the pseudodistance induced by the matrix.     

Generalized double Casoratian solutions to the four-potential isospectral Ablowitz–Ladik equation

Generalized solutions in double Casoratian form of the four-potential isospectral Ablowitz–Ladik equation possessing bilinear form are derived through a matrix method for constructing double Casoratian entries. A novel class of explicit solutions, such as soliton, rational-like, Matveev, Complexiton and interaction solutions, are obtained by letting the general matrix be some special cases. Interestingly, a periodic solution is deduced from the Complexiton solution.     

The local parametric identifiability of a linear stationary system from a single observation of its solution

A special case of a system of linear stationary differential equations depending on a parameter is considered. Necessary and sufficient conditions for the local parametric identifiability of such a system from a single observation of its solution are obtained. Relations between the conditions obtained and the behavior of the spectrum of the matrix of the system are analyzed.     

THE GENERALIZED REFLEXIVE SOLUTION FOR A CLASS OF MATRIX EQUATIONS （AX- B, XC- D）

In this article, the generalized reflexive solution of matrix equations （AX = B, XC = D） is considered. With special properties of generalized reflexive matrices, the necessary and sufficient conditions for the solvability and the general expression of the solution are obtained. Moreover, the related optimal approximation problem to a given matrix over the solution set is solved.     

An analysis of the matrix equation <Emphasis Type="Italic">AX + X̄B = C</Emphasis>

The matrix equation AX + X?B = C, where X?B is obtained by the entry-wise conjugation of X, is examined. On the basis of analogy with the Sylvester matrix equation, special cases are distinguished where the former equation corresponds to normal and self-adjoint Sylvester equations. Efficient numerical algorithms are proposed for these special cases.     

The nullity theorem for principal pivot transform

We generalize the nullity theorem of Gustafson (1984) [8] from matrix inversion to principal pivot transform. Several special cases of the obtained result are known in the literature, such as a result concerning local complementation on graphs. As an application, we show that a particular matrix polynomial, the so-called nullity polynomial, is invariant under principal pivot transform.     

特殊双变量矩阵方程组异类约束解的MCG算法

本文研究了约束矩阵方程问题中异类约束解的迭代算法.利用修正共轭梯度法,求得了特殊双变量线性矩阵方程组的异类约束解,选取特殊的初始矩阵,得到唯一极小范数异类约束解.理论证明和数值算例验证了该方法的有限步收敛性,推广了修正共轭梯度法在求约束矩阵方程问题中的应用范围.     

One class of dual matrix methods

One class of dual matrix methods is given, dependent on three parameters which can be chosen arbitrarily. It is proven that the minimum of a quadratic form with n variables will be obtained in at most n+1 steps in the case of an arbitrary choice of parameters. This method class enables concrete methods to be developed. Finally, it is shown how two known dual matrix methods are obtained as special cases.     

Representation theory of finite groups in Wiener–Hopf factorization problem

We consider the Wiener–Hopf factorization problem for a matrix function that is completely defined by its first column: the succeeding columns are obtained from the first one by means of a finite group of permutations. The symmetry of this matrix function allows us to reduce the dimension of the problem. In particular, we find some relations between its partial indices and can compute some of the indices. In special cases, we can explicitly obtain the Wiener–Hopf factorization of the matrix function.