对称r-循环矩阵的快速算法和并行算法

借助于快速付立叶变换(FFT),给出了一种判断对称r-循环线性系统是否有解的快速算法,并且在有解的情况下求出其解,该算法的计算复杂度为O(nlogn),且具有很好的并行性,若使用n台处理机并行处理该算法则只需要O(logn)步.当r=0时,对称r-循环矩阵变成一个上三角型Hankel矩阵,我们也给出了此类矩阵求逆的一种算法.最后将该算法推广到线性同余系统,其运算量仅为O(nlogn).     

在两循环矩阵类中求解线性方程组反问题的快速算法

本文利用多项式最大公因式 ,给出了线性方程组的反问题在 r-循环矩阵类和对称 r-循环矩阵类中有唯一解的充要条件 ,进而得到线性方程组在 r循环矩阵类和对称 r-循环矩阵类中的反问题求唯一解的算法 .最后给出了应用该算法的数值例子 .     

两类r-循环矩阵求逆的快速算法

本文利用多项式的最大公因式给出的求r-循环矩阵和对称r-循环矩阵求逆的快速算法。该方法不需要计算三角函数并且具有很少的计算量。     

奇异模糊线性系统的扰动分析

当模糊线性系统的系数矩阵奇异时, 分析了模糊线性系统的右端向量和系数矩阵的扰动对模糊线性系统解的计算造成的影响,用矩阵的谱范数给出了相对误差的界.     

求首尾和r-循环矩阵的极小多项式的算法

研究了域上首尾和r-循环矩阵，利用多项式环的理想的Groebner基的算法给出了任意域上首尾和r-循环矩阵的极小多项式和公共极小多项式的一种算法.同时给出了这类矩阵逆矩阵的一种求法。     

r-对称循环矩阵及逆矩阵三角分解的快速算法

根据r-对称循环矩阵的特殊结构给出了求这类矩阵本身及其逆矩阵三角分解的快速算法,算法的运算量均为O(n2),一般矩阵及逆矩阵三角分解的运算量均为O(n3).     

图的（k，d）-着色问题的一个近似算法

本文讨论了图的(k,d)-着色问题的算法,并给出了一个由四层神经元组成的神经网络算法.当一个图的循环色数已知时(不妨设为k/d),可以利用该算法成功地求出这个图的一个可行(k,d)-着色方案;当一个图的循环色数未知时,可以利用该算法求出这个图的循环色数的近似值.     

关于三元r-循环实矩阵及其应用

讨论三元 r-循环实矩阵 ,给出了三元 r-循环实矩阵的行列式和逆矩阵的实表达式 .从而得到r-循环实矩阵的行列式和逆矩阵的实表达式     

关于第二类r-循环矩阵求逆的一种算法

利用矩阵的初等行变换给出可逆的第二类r-循环矩阵的求逆的简便算法．     

一种改进的线性系统的有限时间平衡截断（英文）

本文提出一种改进的线性系统的有限时间平衡截断方法.该方法首先利用Shifted Legendre多项式对线性系统的有限时间可控Gram矩阵和可观Gram矩阵进行近似低秩分解,其中根据正交多项式与幂级数之间的关系,该近似低秩分解因子可以通过简单的递推公式得到,然后构造正交投影变换得到近似平衡系统,进而通过截断较小的Hankel奇异值对应的状态得到降阶系统.此外,本文还简要讨论了该降阶模型的稳定性.最后,通过数值算例验证了算法的有效性.     

Accelerate overrelaxation methods for rank deficient linear systems

In this paper, we apply accelerated overrelaxation (AOR) methods to find the least square solution of minimal norm to the linear system

Ay=b

where is a matrix of rank r and . We first augment the system to a block 4×4 consistent system, and then split the augmented coefficient matrix by AOR subproper splitting. Intervals for the two relaxation parameters where the AOR iteration matrix is semiconvergent are presented. Also, we provide a method to compute the least square solution of minimal norm to the system.     

一类广义Lyapunov矩阵方程的正定解

研究了双线性系统中的一类广义Lyapunov矩阵方程的正定解.基于混合单调算子不动点定理,给出新的存在正定解的充分条件,构造了求其正定解的不动点迭代方法,并给出了迭代误差估计公式.数值实验表明新方法是可行的.     

A class of discrete time generalized Riccati equations

In this paper, a class of discrete-time backward non-linear equations defined on some ordered Hilbert spaces of symmetric matrices is considered. The problem of the existence of some global solutions is investigated. The class of considered discrete-time non-linear equations contains, as special cases, a great number of difference Riccati equations both from the deterministic and the stochastic framework. The results proved in the paper provide the sets of necessary and sufficient conditions that guarantee the existence of some special solutions of the considered equations as: the maximal solution, the stabilizing solution and the minimal positive semi-definite solution. These conditions are expressed in terms of the feasibility of some suitable systems of linear matrix inequalities (LMI). One shows that in the case of the equations with periodic coefficients to verify the conditions that guarantee the existence of the maximal or the stabilizing solution, we have to check the solvability of some systems of LMI with a finite number of inequations. The proofs are based on some suitable properties of discrete-time linear equations defined by the positive operators on some ordered Hilbert spaces chosen adequately. The results derived in this paper provide useful conditions that guarantee the existence of the maximal solution or the stabilizing solution for different classes of difference matrix Riccati equations involved in many problems of robust control both in the deterministic and the stochastic framework. The proofs are deterministic and are accessible to the readers less familiarized with the stochastic reasonings.     

The solution of linear systems by using the Sherman–Morrison formula

We consider the problem of solving the linear system Ax = b, where A is the coefficient matrix, b is the known right hand side vector and x is the solution vector to be determined. Let us suppose that A is a nonsingular square matrix, so that the linear system Ax = b is uniquely solvable.

The well known Sherman–Morrison formula, that gives the inverse of a rank-one perturbation of a matrix from the knowledge of the unperturbed inverse matrix, is used to compute the numerical solution of arbitrary linear systems, in fact it can be repetitively applied to invert an arbitrary matrix. We describe some interesting properties of the method proposed.

Finally we show some numerical results obtained with the method proposed.     

Super-fast validated solution of linear systems

Validated solution of a problem means to compute error bounds for a solution in finite precision. This includes the proof of existence of a solution. The computed error bounds are to be correct including all possible effects of rounding errors. The fastest known validation algorithm for the solution of a system of linear equations requires twice the computing time of a standard (purely) numerical algorithm. In this paper we present a super-fast validation algorithm for linear systems with symmetric positive definite matrix. This means that the entire computing time for the validation algorithm including computation of an approximated solution is the same as for a standard numerical algorithm. Numerical results are presented.     

关于r-分块循环矩阵及其对角化问题的探讨

本文给出了r-分块循环矩阵的概念,并利用矩阵的张量积探讨了r-分块循环矩阵的相似类及其对角化问题,得出了一些重要的结论.     

Newton iterations in implicit time-stepping scheme for differential linear complementarity systems

We propose a generalized Newton method for solving the system of nonlinear equations with linear complementarity constraints in the implicit or semi-implicit time-stepping scheme for differential linear complementarity systems (DLCS). We choose a specific solution from the solution set of the linear complementarity constraints to define a locally Lipschitz continuous right-hand-side function in the differential equation. Moreover, we present a simple formula to compute an element in the Clarke generalized Jacobian of the solution function. We show that the implicit or semi-implicit time-stepping scheme using the generalized Newton method can be applied to a class of DLCS including the nondegenerate matrix DLCS and hidden Z-matrix DLCS, and has a superlinear convergence rate. To illustrate our approach, we show that choosing the least-element solution from the solution set of the Z-matrix linear complementarity constraints can define a Lipschitz continuous right-hand-side function with a computable Lipschitz constant. The Lipschitz constant helps us to choose the step size of the time-stepping scheme and guarantee the convergence.     

The efficient solution of electromagnetic scattering for inhomogeneous media

We consider an electromagnetic scattering problem for inhomogeneous media. In particular, we focus on the numerical computation of the electromagnetic scattered wave generated by the interaction of an electromagnetic plane wave and an inhomogeneity in the corresponding propagation medium. This problem is studied in the VV polarization case, where some special symmetry requirements for the incident wave and for the inhomogeneity are assumed. This problem is reformulated as a Fredholm integral equation of second kind, which is discretized by a linear system having a special form. This allows to compute efficiently an approximate solution of the scattering problem by using iterative techniques for linear systems. Some numerical examples are reported.     

A parallel algorithm for solving Toeplitz linear systems

Numerical methods of solution are considered for systems which are Toeplitz and symmetric. In our case, the coefficient matrix is essentially tridiagonal and sparse. There are two distinct approaches to be considered each of which is efficient in its own way. Here we will combine the two approaches which will allow application of the cyclic reduction method to coefficient matrices of more general forms. The convergence of the approximations to the exact solution will also be examined. Solving linear systems by the adapted cyclic reduction method can be parallel processed.