求解连续Sylvester矩阵方程的E-extra迭代法

本文提出一种求解连续Sylvester方程的E-extra迭代法,分析该方法的收敛性,给出最优参数的选取方法.并通过几个数值实例验证了E-extra迭代法的有效性.     

基于分数阶扩散方程的离散线性代数方程组迭代方法研究

本文构建一类双参数拟Toeplitz分裂（TQTS）迭代方法求解变系数非定常空间分数阶扩散方程.TQTS迭代法是基于QTS迭代法引入双参技术建立而成,通过选取适当的参数使迭代矩阵谱半径变得更小,从而有效提升收敛的速度.然后对TQTS迭代法进行收敛性分析,获得相应的收敛区域,并对迭代法中涉及的参数进行讨论,获得使迭代矩阵谱半径上界达到最小的最优参数的表达式.最后通过数值仿真实验验证TQTS迭代法的有效性,实验结果表明TQTS迭代法改进效果十分突出,在迭代时间和步数上均有明显的减小.     

广义Lyapunov方程的HSS迭代法

提出了求解广义Lyapunov方程的HSS(Hermitian and skew-Hermitian splitting)迭代法,分析了该方法的收敛性,给出了收敛因子的上界.为了降低HSS迭代法的计算量,提出了求解广义Lyapunov方程的非精确HSS迭代法,并分析其收敛性.数值结果表明,求解广义Lyapunov方程的HSS迭代法及非精确HSS迭代法是有效的.     

M-矩阵代数Riccati方程的一类新的迭代解法

本文研究M-矩阵代数Riccati方程的数值解法.利用适当的变换将方程转化为其离散形式,进而提出了一种新的迭代法来计算方程的最小非负解.通过选取合适的迭代参数,证明了新方法的收敛性.理论分析和数值实验表明,新方法是可行的,而且在一定情况下比现有的几类方法更加有效.     

连续Sylvester方程的广义正定和反Hermitian分裂迭代法及其超松弛加速

对于求解大型稀疏连续Sylvester方程,Bai提出了非常有效的Hermitian和反Hermitian分裂(HSS)迭代法.为了进一步提高求解这类方程的效率,本文建立一种广义正定和反Hermitian分裂(GPSS)迭代法,并且提出不精确GPSS(IGPSS)迭代法从而可以降低计算成本.对GPSS迭代法及其不精确变...     

变分同伦摄动迭代法求解抛物型方程反问题中的控制参数北大核心CSCD

变分同伦摄动迭代法是结合变分迭代法和同伦摄动法而产生的新方法,被应用于求解含有未知参数的线性抛物型方程反问题.通过该方法,可以快速得到收敛于反问题精确解的收敛序列.本文通过一些实例,来验证说明该方法的高效性和可靠性.     

变分同伦摄动迭代法求解抛物型方程反问题中的控制参数

变分同伦摄动迭代法是结合变分迭代法和同伦摄动法而产生的新方法,被应用于求解含有未知参数的线性抛物型方程反问题.通过该方法,可以快速得到收敛于反问题精确解的收敛序列.本文通过一些实例,来验证说明该方法的高效性和可靠性.     

变厚度圆薄板在均布载荷下大挠度问题

本文首先给出变厚度圆薄板大挠度方程,用小参数方法和修正迭代法联合求解此问题,得到三次近似解;给出特征曲线同线性理论进行了比较.     

分数阶振子方程基于变分迭代的近似解析解序列

在粘弹性介质中的阻尼振动中引入分数阶微分算子,建立分数阶非线性振动方程.使用了分数阶变分迭代法（FVIM）,推导了Lagrange乘子的若干种形式.对线性分数阶阻尼方程,分别对齐次方程和正弦激励力的非齐次方程应用FVIM得到近似解析解序列.以含激励的Bagley-Torvik方程为例,给出不同分数阶次的位移变化曲线.研究了振子运动与方程中分数阶导数阶次的关系,这可由不同分数阶次下记忆性的强弱来解释.计算方法上,与常规的FVIM相比,引入小参数的改进变分迭代法能够大大扩展问题的收敛区段.最后,以一个含分数导数的Van der Pol方程为例说明了FVIM方法解决非线性分数阶微分问题的有效性和便利性.     

延迟积分-微分方程的敏感度和Hopf分岔分析

本文考虑了一类延迟积分-微分方程的Hopf分岔分析.利用敏感性方程,确定了一个合适的Hopf参数.基于Hopf分岔理论得到,当系统存在Hopf分岔时系统参数必须满足的条件.为了得到Hopf参数的精确值,进一步讨论了延迟积分-微分方程的离散形式,利用Newton迭代法,得到了参数的逼近值.最后,数值仿真说明了我们的理论的有效性.     

Iterative solutions to coupled Sylvester-transpose matrix equations

This note studies the iterative solutions to the coupled Sylvester-transpose matrix equation with a unique solution. By using the hierarchical identification principle, an iterative algorithm is presented for solving this class of coupled matrix equations. It is proved that the iterative solution consistently converges to the exact solution for any initial values. Meanwhile, sufficient conditions are derived to guarantee that the iterative solutions given by the proposed algorithm converge to the exact solution for any initial matrices. Finally, a numerical example is given to illustrate the efficiency of the proposed approach.     

Construction and Structure Properties of Solutions of a Periodic Boundary Value Problem for a Generalization of the Matrix Lyapunov and Riccati Equations

We obtain constructive sufficient conditions for the unique solvability of a periodic boundary value problem for a matrix differential equation that generalizes the Lyapunov and Riccati equations, develop an algorithm for constructing the solution of this equation, estimate the domain where the solution is localized, and study the structural properties of the solution.     

Multipoint boundary value problem for the Lyapunov equation in the case of strong degeneration of the boundary conditions

We obtain sufficient coefficient conditions for the unique solvability of a multipoint boundary value problem for the Lyapunov matrix differential equation in the case of strong degeneration of the boundary conditions. We suggest an efficient algorithm for constructing the solution.     

A conservative bound on the estimation error covariance matrix in the presence of correlated driving noise and correlated discrete measurement noise

In an earlier paper, the conservative and minimal bound to the crosscorrelation terms between estimation error and a random forcing function was presented. That bound was found to be a particular linear combination of the estimation error covariance and the forcing function covariance involving a free scalar parameter. The bound was then substituted for the cross-correlation terms in the differential equation for the estimation error covariance matrix in order to approximate its behavior between discrete measurement times. The time history of the free parameter which minimized a linear combination of the elements of the estimated covariance matrix at the next measurement time was found as the noniterative solution to an optimal control problem with a matrix state.In this paper, necessary and sufficient conditions are presented for the problem of minimizing a linear combination of the elements of the approximated estimation error covariance at the end of an interval in which are linearly incorporated a finite number of discrete vector measurements corrupted by white and/or correlated measurement noise. Although the determination of the optimal trajectory in general requires iteration, a particularly simple algorithm is presented. Numerical results are presented for the case of a satellite in a highly elliptic orbit about a model Earth.     

矩阵方程AX=B的转动不变解及其最佳逼近

利用矩阵的广义逆、奇异值分解、张量积和拉直算子,给出了矩阵方程AX=B有转动不变解的充分必要条件及有解时通解的表达式;给出了矩阵方程解集合中与给定矩阵的最佳逼近解的表达式.     

Least squares solution with the minimum-norm to general matrix equations via iteration

Two iterative algorithms are presented in this paper to solve the minimal norm least squares solution to a general linear matrix equations including the well-known Sylvester matrix equation and Lyapunov matrix equation as special cases. The first algorithm is based on the gradient based searching principle and the other one can be viewed as its dual form. Necessary and sufficient conditions for the step sizes in these two algorithms are proposed to guarantee the convergence of the algorithms for arbitrary initial conditions. Sufficient condition that is easy to compute is also given. Moreover, two methods are proposed to choose the optimal step sizes such that the convergence speeds of the algorithms are maximized. Between these two methods, the first one is to minimize the spectral radius of the iteration matrix and explicit expression for the optimal step size is obtained. The second method is to minimize the square sum of the F-norm of the error matrices produced by the algorithm and it is shown that the optimal step size exits uniquely and lies in an interval. Several numerical examples are given to illustrate the efficiency of the proposed approach.     

Filtering-based robust fault detection of fuzzy jump systems

This paper studies the robust fault detection filter (RFDF) design problems for uncertain nonlinear Markov jump systems with state delays and parameter uncertainties. By means of Takagi-Sugeno fuzzy models, the dynamics of filtering error generator and the fuzzy RFDF system are constructed. With the aid of the selected weighting matrix function, the design objective is to find an optimal RFDF which results in a minimal difference between the reference model (ideal solution) and the RFDF (real solution) to be designed. A sufficient condition is firstly established on the stochastic stability by using stochastic Lyapunov-Krasovskii functional approach. Then in terms of linear matrix inequalities techniques, sufficient conditions on the existence of fuzzy RFDF are presented and proved. Finally, the design problem is formulated as an optimization algorithm. Simulation results illustrate that the proposed RFDF can detect the faults shortly after the occurrences.     

二次矩阵方程AX~2+BX+C=0的可对角化解

给出了二次矩阵方程AX2+BX+C=0的特征值和特征子空间的定义,然后运用其特征子空间的维数或特征向量刻画了该二次矩阵方程存在可对角化解的充要条件.     

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 .     

The solvability conditions for inverse problems of anti-symmetric ortho-symmetric matrices

This paper discusses the anti-symmetric ortho-symmetric solution of a linear matrix equation and its optimal approximation. The necessary and sufficient conditions for the solvability of the matrix equation and the general expression of the anti-symmetric ortho-symmetric solution are given. In addition, the existence and uniqueness of the optimal approximation are proved. Numerical methods of the optimal approximation to a given matrix and numerical experiments are described.