用试验数据修正振动系统的双对称阻尼矩阵与刚度矩阵

讨论用试验数据修正振动系统的双对称阻尼矩阵与刚度矩阵问题.依据特征方程、阻尼矩阵与刚度矩阵的双对称性,利用代数二次特征值反问题的理论和方法,研究了该问题解的存在性与唯一性,提出了修正阻尼矩阵与刚度矩阵的一个新方法.利用双对称矩阵的性质研究了方程的双对称解.给出了二次特征值反问题双对称解的一般表达式,讨论了对任意给定矩阵的最佳逼近问题,并给出了问题的最佳逼近解.用该方法修正的阻尼矩阵与刚度矩阵不仅满足二次特征方程,而且是唯一的双对称矩阵.     

矩阵方程X—A*X~qA=I(0＜q＜1)Hermite正定解的扰动分析

首先证明了非线性矩阵方程X-A~*X~qA=I(0相似文献   

求解四元数矩阵方程X-AXB=CY+D的一种新方法（英文）

提出了四元数矩阵的一种实向量表示法,可以结合矩阵的半张量积研究四元数矩阵方程.给出了四元数矩阵方程X-AXB=CY+D的最小二乘Hermitian解的通解表达式,以及该方程具有Hermitian解的充要条件,通过数值实验,验证该方法的有效性.     

一类四元数受限矩阵表达式的最大秩（英文）

确立了一类分块矩阵M11 M12 XM21 M22 M23Y M32 M33的最大秩公式,其中,X和Y是两个受限于四元数线性矩阵方程A_1X=C_1,XB_1=C_2,A_3XB_3=C_3,A_2Y=D_1,YB_2=D_2.的变量矩阵。作为该公式的一项应用,我们推导出上述矩阵方程解集等同于另一四元数二次矩阵方程组解集的条件。     

一类矩阵方程的对称次反对称解及其最佳逼近

利用矩阵的广义奇异值分解 ,得到了矩阵方程 ATXA =B有对称次反对称解的充分必要条件及其通解的表达式 ,并且给出了在矩阵方程的解集合中与给定矩阵的最佳逼近解的表达式 .     

矩阵方程AXB=D的(R,S)-斜对称解

矩阵方程AXB=D是教学、理论研究和工程实践中常见的一种矩阵方程.给出了AXB=D具有(R,S)-斜对称矩阵解的充分必要条件,及其解存在条件下全体解集合S_X的表达式.此外,还讨论了任意给定矩阵X在仿射子空间S_X中的最优近似解,并给出了最优解的显示表达式.     

一类矩阵方程的埃尔米特自反最小二乘解

利用埃尔米特自反矩阵的表示定理和矩阵的拉直方法,研究了矩阵方程$AX+BY=C$的埃尔米特自反最小二乘问题,进一步,给出了方程在埃尔米特自反矩阵集合中可解的充分必要条件,得到解的一般表达式,最后,对任意给定的一对复矩阵,得到了其相关最佳逼近问题解的表达式.     

与M-矩阵相关的一类二次矩阵方程的新迭代法（英文）

本文研究与M-矩阵相关的一类二次矩阵方程的数值解法.这类方程源于马尔可夫链的带噪Wiener-Hopf问题,其解中具有实际意义的是M-矩阵解.通过简单的变换,将该二次矩阵方程转化为M-矩阵代数Riccati方程.提出一种新的迭代方法,并对其进行收敛性分析.数值实验表明,新的迭代方法是可行的,且在一定条件下比现有的一些方法更为有效.     

矩阵方程A×B=D的(R,S)-斜对称解

矩阵方程A×B=D是教学、理论研究和工程实践中常见的一种矩阵方程.给出了A×B=D具有(R,S)-斜对称矩阵解的充分必要条件,及其解存在条件下全体解集合Sx的表达式.此外,还讨论了任意给定矩阵(X)在仿射子空间Sx中的最优近似解,并给出了最优解的显示表达式.     

四元数矩阵方程AX+YA=C的两种最佳逼近解

利用四元数矩阵的广义Frobenius范数建立一个关于四元数矩阵的实函数,并讨论了它的极值问题,然后在四元数矩阵方程AX YA=C的一般解和自共轭解集合中分别导出了与给定相同类型矩阵的最佳逼近解的表达式.     

ON THE MINIMAL NONNEGATIVE SOLUTION OF ONSYMMETRIC ALGEBRAIC RICCATI EQUATION

We study perturbation bound and structured condition number about the minimalnonnegative solution of nonsymmetric algebraic Riccati equation,obtaining a sharp per-turbation bound and an accurate condition number.By using the matrix sign functionmethod we present a new method for finding the minimal nonnegative solution of this al-gebraic Riccati equation.Based on this new method,we show how to compute the desiredM-matrix solution of the quadratic matrix equation X~2-EX-F=0 by connecting itwith the nonsymmetric algebraic Riccati equation,where E is a diagonal matrix and F isan M-matrix.     

矩阵方程X-A~*X~(-1)A=Q的Hermite正定解及其扰动分析

考虑非线性矩阵方程X-A*X-1A=Q,其中A是n阶复矩阵,Q是n阶Hermite正定解,A*是矩阵A的共轭转置.本文证明了此方程存在唯一的正定解,并推导出此正定解的扰动边界和条件数的显式表达式.以上结果用数值例子加以说明.     

On the Minimal Nonnegative Solution of Nonsymmetric Algebraic Riccati Equation

We study perturbation bound and structured condition number about the minimal nonnegative solution of nonsymmetric algebraic Riccati equation, obtaining a sharp perturbation bound and an accurate condition number. By using the matrix sign function method we present a new method for finding the minimal nonnegative solution of this algebraic Riccati equation. Based on this new method, we show how to compute the desired M-matrix solution of the quadratic matrix equation X^2 - EX - F = 0 by connecting it with the nonsymmetric algebraic Riccati equation, where E is a diagonal matrix and F is an M-matrix.     

Perturbation analysis of the matrix equation

Consider the nonlinear matrix equation X-A^*X^-pA=Q with 0<p1. This paper shows that there exists a unique positive definite solution to the equation. A perturbation bound and the backward error of an approximate solution to this solution is evaluated. We also obtain explicit expressions of the condition number for the unique positive definite solution. The theoretical results are illustrated by numerical examples.     

Markovian quadratic and superquadratic BSDEs with an unbounded terminal condition

This article deals with the existence and the uniqueness of solutions to quadratic and superquadratic Markovian backward stochastic differential equations (BSDEs) with an unbounded terminal condition. Our results are deeply linked with a strong a priori estimate on Z$Z$ that takes advantage of the Markovian framework. This estimate allows us to prove the existence of a viscosity solution to a semilinear parabolic partial differential equation with nonlinearity having quadratic or superquadratic growth in the gradient of the solution. This estimate also allows us to give explicit convergence rates for time approximation of quadratic or superquadratic Markovian BSDEs.     

Backward error,sensitivity, and refinement of computed solutions of algebraic Riccati equations

In this paper, a new backward error criterion, together with a sensitivity measure, is presented for assessing solution accuracy of nonsymmetric and symmetric algebraic Riccati equations (AREs). The usual approach to assessing reliability of computed solutions is to employ standard perturbation and sensitivity results for linear systems and to extend them further to AREs. However, such methods are not altogether appropriate since they do not take account of the underlying structure of these matrix equations. The approach considered here is to first compute the backward error of a computed solution X? that measures the amount by which data must be perturbed so that X? is the exact solution of the perturbed original system. Conventional perturbation theory is used to define structured condition numbers that fully respect the special structure of these matrix equations. The new condition number, together with the backward error of computed solutions, provides accurate estimates for the sensitivity of solutions. Optimal perturbations are then used in an iterative refinement procedure to give further more accurate approximations of actual solutions. The results are derived in their most general setting for nonsymmetric and symmetric AREs. This in turn offers a unifying framework through which it is possible to establish similar results for Sylvester equations, Lyapunov equations, linear systems, and matrix inversions.     

Rounding Error Analysis in Solving M-Matrix Linear Systems of Block Hessenberg Form

The problem of solving large M-matrix linear systems with sparse coefficient matrix in block Hessenberg form is here addressed. In previous work of the authors a divide-and-conquer strategy was proposed and a backward error analysis of the resulting algorithm was presented showing its effectiveness for the solution of computational problems of queueing theory and Markov chains. In particular, it was shown that for block Hessenberg M-matrices the algorithm is weakly backward stable in the sense that the computed solution is the exact solution of a nearby linear system, where the norm of the perturbation is proportional to the condition number of the coefficient matrix. In this note a better error estimate is given by showing that for block Hessenberg M-matrices the algorithm is even backward stable.     

An Indefinite Stochastic Linear Quadratic Optimal Control Problem with Delay and Related Forward–Backward Stochastic Differential Equations

In this paper, we will study an indefinite stochastic linear quadratic optimal control problem, where the controlled system is described by a stochastic differential equation with delay. By introducing the relaxed compensator as a novel method, we obtain the well-posedness of this linear quadratic problem for indefinite case. And then, we discuss the uniqueness and existence of the solutions for a kind of anticipated forward–backward stochastic differential delayed equations. Based on this, we derive the solvability of the corresponding stochastic Hamiltonian systems, and give the explicit representation of the optimal control for the linear quadratic problem with delay in an open-loop form. The theoretical results are validated as well on the control problems of engineering and economics under indefinite condition.     

The structured sensitivity of Vandermonde-like systems

Summary We consider a general class of structured matrices that includes (possibly confluent) Vandermonde and Vandermonde-like matrices. Here the entries in the matrix depend nonlinearly upon a vector of parameters. We define, condition numbers that measure the componentwise sensitivity of the associated primal and dual solutions to small componentwise perturbations in the parameters and in the right-hand side. Convenient expressions are derived for the infinity norm based condition numbers, and order-of-magnitude estimates are given for condition numbers defined in terms of a general vector norm. We then discuss the computation of the corresponding backward errors. After linearising the constraints, we derive an exact expression for the infinity norm dual backward error and show that the corresponding primal backward error is given by the minimum infinity-norm solution of an underdetermined linear system. Exact componentwise condition numbers are also derived for matrix inversion and the least squares problem, and the linearised least squares backward error is characterised.