病态代数方程求解的一种改进精细积分法

通过在病态代数方程精细积分法的基础上增加一个迭代改善算法,建立了病态代数方程求解的改进精细积分法．该方法进一步提高了病态代数方程精细积分法的精度和效率,具有良好的应用前景．算例证明了该方法在病态代数方程求解中的有效性．     

灰色系统模型病态矩阵的双正则化算法

灰色系统模型矩阵会存在病态问题.为消除其病态性,基于病态矩阵的双正则化方法,建立了正则化灰色系统模型中灰参数求解的表达式,给出了其导出方式;提出了正则参数α的选择原则.从而避免了灰参数求解过程中矩阵的病态问题.数值试验分析说明,灰色系统模型的双正则化算法是正确和适用的.     

结构动力方程求解的改进-精细Runge-Kutta方法

在已有精细Runge-Kutta(龙格-库塔)方法的基础上,考虑了状态空间方程非齐次项的特点和外荷载的特殊性,提出了求解结构动力方程的改进精细Runge-Kutta方法.通过对矩阵进行分块计算,在利用原有精细Runge-Kutta方法高精度的同时进一步提高了计算效率,有利于大型结构的长时间仿真.将改进精细Runge-Kutta方法应用于结构动力方程求解,为其求解提供一种新方法.数值算例表明了改进方法的正确性和有效性.     

基于时域精细积分算法的瞬态传热多宗量反演

基于有限元法和精细积分算法,提出了一种求解瞬态热传导多宗量反演问题的新方法．采用有限元法和精细积分算法分别对空间、时间变量进行离散,可以得到正演问题高精度的半解析数值模型,由此建立了多宗量反演的计算模式,并给出敏度分析的计算公式．对一维和二维的热物性参数、热源项、边界条件等进行了单宗量和多宗量的反演求解,初步考虑了初值和噪音等对反演结果的影响,数值算例验证了该方法的有效性．     

求解奇异摄动边值问题的精细积分法

提出了一种求解一端有边界层的奇异摄动边值问题的精细方法．首先将求解区域均匀离散,由状态参量在相邻节点间的精细积分关系式确定一组代数方程,并将其写成矩阵形式．代入边界条件后,该代数方程组的系数矩阵可化为块三对角形式,针对这一特性,给出了一种高效递推消元方法．由于在离散过程中,精细积分关系式不会引入离散误差,故所提出的方法具有极高的精度．数值算例充分证明了所提出方法的有效性．     

线性定常系统非齐次两点边值问题的扩展精细积分方法

提出了一种求解非齐次线性两点边值问题的高精度和高稳定的扩展精细积分方法（EPIM）.首先引入了区段量（即区段矩阵和区段向量）来离散非齐次线性微分方程,建立了非齐次两点边值问题基于区段量的求解框架.在该框架下,不同区段的区段量可以并行计算,整体代数方程组的集成不依赖于边界条件.然后引入区段响应矩阵来处理两点边值问题的非齐次项,导出了多项式函数、指数函数、正/余弦函数及其组合函数形式的非齐次项对应的区段响应矩阵的加法定理,结合增量存储技术提出了EPIM.对具有上述函数形式的非齐次项,该方法可以得到计算机上的精确解,一般形式的非齐次项则利用上述函数近似求解.最后通过两个具有刚性特征的数值算例验证了该方法的高精度和高稳定性.     

求解病态线性方程组的预处理精细积分法

为降低病态线性方程组系数矩阵的条件数,根据矩阵行(列)均衡的思想,提出行(列)的1-范数均衡法,并扩展为范数均衡法.然后,将范数均衡法与精细积分法相结合,给出求解病态线性方程组的范数均衡预处理精细积分法.数值结果表明,经过范数均衡预处理后精细积分法求解病态方程的精度(有效数字增加5个以上)和效率(迭代次数降低15次左右)均能得到显著提高,适用范围在一定程度上也有所扩展.在上述方法中,以1-范数均衡预处理精细积分法效果最为显著.     

基于超松弛预处理的精细积迭代反演算法

电磁波、声波层析成像技术在地质探测等很多领域有了广泛应用,其中反演算法在层析成像过程中处于核心地位,反演算法的优劣将直接关系层析成像的成败.给出了一种基于超松弛预处理的精细积分迭代反演算法,算法将方程组求解归结为一个常微分方程组初值问题的极限形式,对以此为基础建立的递推算法中指数矩阵利用精细积分法计算,但在此之前利用超松弛法将正演所得病态矩阵预处理,降低条件数以减少测量扰动对反演计算的影响.通过检测板模型恢复测试以及实际资料反演结果比较,预处理精细积分方法在准确性和稳定性上都具有一定的优势,在迭代次数较少时即能得到分辨率较高的反演速度剖面;另外,过程中参数的选择具有一定任意性,同时规则网格尺度可以根据折射初至时数目灵活选取,具有更强的实用性.     

改进的预处理共轭斜量法及其在工程有限元分析中的应用

本文就预处理共轭斜量法(PCCG法)给出了两个具有理论和实际意义的定理,它们分别讨论了迭代解的定性性质和迭代矩阵的构造原则.作者提出了新的非M-矩阵的不完全LU分解技术和迭代矩阵的构造方法.用此改进的PCCG法,对病态问题和大型三维有限元问题进行了计算并与其他方法作了对比,分析了PCCG法在求解病态方程组时的反常现象.计算结果表明本文建议的方法是求解大型有限元方程组和病态方程组的一种十分有效的方法.     

区间参数结构振动问题的矩阵摄动法

当结构的参数具有不确定性时，结构的固有频率也将具有某种程度的不确定性．本文讨论了区间参数结构的振动问题，将区间参数结构的特征值问题归结为两个不同的特征值问题来求解．提出了求解区间参数结构振动问题的矩阵摄动方法．数值运算结果表明，本文所提出方法具有运算量小，结果精度高等优点．     

影响阻尼牛顿法收敛性的两个重要参数

对阻尼牛顿算法作了适当的改进,证明了新算法的收敛性.基于新算法,运用计算机代数系统Matlab,研究了迭代次数k,参数对(μ,λ)与初值x0三者间的依赖关系,研究了病态问题在新算法下趋于稳定的渐变(瞬变)过程.数值结果表明:(1)阻尼牛顿迭代中,参数对(μ,λ)与迭代次数k间存在特有的非线性关系;(2)适当的参数对(μ,λ)与阻尼因子α的共同作用能够在迭代中大幅度地降低病态问题的Jacobi阵的条件数,使病态问题逐渐趋于稳定,从而改变原问题的收敛性与收敛速度.     

泛最小二乘法的改进及其容许性

考虑线性回归模型,当设计阵呈病态或秩亏时,我们用泛最小二乘法给出参数的估计,并证明其容许性;然后针对泛最小二乘估计对最小二乘估计过度压缩的缺点加以改进,使之更合理,有效.     

非对称矩阵的病态特征向量的约化

1.引言 关于密集特征值与其病态特征向量之间的内在联系,Varah(1970),Wilkinson(1972及1984)和Kahan(1970)曾经研究过.Varah(1970)最先指出:若矩阵A具有二阶以上的Jordan块,且当A加上一个扰动矩阵(?=A+E)则相似于对角阵时,其相似变换矩阵是病态的(即变换矩阵各列几乎线性相关).Varah对于病态的程度,给予了数     

A SHIFT-SPLITTING PRECONDITIONER FOR NON-HERMITIAN POSITIVE DEFINITE MATRICES

A shift splitting concept is introduced and, correspondingly, a shift-splitting iteration scheme and a shift-splitting preconditioner are presented, for solving the large sparse system of linear equations of which the coefficient matrix is an ill-conditioned non-Hermitian positive definite matrix. The convergence property of the shift-splitting iteration method and the eigenvalue distribution of the shift-splitting preconditioned matrix are discussed in depth, and the best possible choice of the shift is investigated in detail. Numerical computations show that the shift-splitting preconditioner can induce accurate, robust and effective preconditioned Krylov subspace iteration methods for solving the large sparse non-Hermitian positive definite systems of linear equations.     

Convergence of Rump's method for inverting arbitrarily ill-conditioned matrices

In this paper, the problem of inverting regular matrices with arbitrarily large condition number is treated in double precision defined by IEEE 754 floating point standard. In about 1984, Rump derived a method for inverting arbitrarily ill-conditioned matrices. The method requires the possibility to calculate a dot product in higher precision. Rump's method is of theoretical interest. Rump made it clear that inverting an arbitrarily ill-conditioned matrix in single or double precision does not produce meaningless numbers, but contains a lot of information in it. Rump's method uses such inverses as preconditioners. Numerical experiments exhibit that Rump's method converges rapidly for various matrices with large condition numbers. Why Rump's method is so efficient for inverting arbitrarily ill-conditioned matrices is a little mysterious. Thus, to prove its convergence is an interesting problem in numerical error analysis. In this article, a convergence theorem is presented for a variant of Rump's method.     

Method of particular solutions using polynomial basis functions for the simulation of plate bending vibration problems

The traditional polynomial expansion method is deemed to be not suitable for solving two- and three-dimensional problems. The system matrix is usually singular and highly ill-conditioned due to large powers of polynomial basis functions. And the inverse of the coefficient matrix is not guaranteed for the evaluation of derivatives of polynomial basis functions with respect to the differential operator of governing equations. To avoid these troublesome issues, this paper presents an improved polynomial expansion method for the simulation of plate bending vibration problems. At first, the particular solutions using polynomial basis functions are derived analytically. Then these polynomial particular solutions are employed as basis functions instead of the original polynomial basis functions in the method of particular solutions for the approximated solutions. To alleviate the conditioning of the resultant matrix, we employ the multiple-scale method. Numerical experiments compared with analytical solutions, solutions by the Kansa’s method, and reference solutions in references confirm the efficiency and accuracy of the proposed method in the solution of Winkler and thin plate bending problems including irregular shapes.     

Numerical solution to the deflection of thin plates using the two-dimensional Berger equation with a meshless method based on multiple-scale Pascal polynomials

In this study, we employ Pascal polynomial basis in the two-dimensional Berger equation, which is a fourth order partial differential equation with applications to thin elastic plates. The polynomial approximation method based on Pascal polynomial basis can be readily adapted to obtain the numerical solutions of partial differential equations. However, a drawback with the polynomial basis is that the resulting coefficient matrix for the problem considered may be ill-conditioned. Due to this ill-conditioned behavior, we use a multiple-scale Pascal polynomial method for the Berger equation. The ill-conditioned numbers can be mitigated using this approach. Multiple scales are established automatically by selecting the collocation points in the multiple-scale Pascal polynomial method. This method is also a meshless method because there is no requirement to establish complex grids or for numerical integration. We present the solutions of six linear and nonlinear benchmark problems obtained with the proposed method on complexly shaped domains. The results obtained demonstrate the accuracy and effectiveness of the proposed method, as well showing its stability against large noise effects.     

A 2-block semi-proximal ADMM for solving the H-weighted nearest correlation matrix problem

Higham considered two types of nearest correlation matrix (NCM) problems, namely the W-weighted case and the H-weighted case. Since there exists well-defined computable formula for the projection onto the symmetric positive semidefinite cone under the W-weighting, it has been well studied to make several Lagrangian dual-based efficient numerical methods available. But these methods are not applicable for the H-weighted case mainly due to the lack of a computable formula. The H-weighted case remains numerically challenging, especially for the highly ill-conditioned weight matrix H. In this paper, we aim to solve the dual form of the H-weighted NCM problem, which has three separable blocks in the objective function with the second part being linear. Based on the linear part, we reformulate it as a new problem with two separable blocks, and introduce the 2-block semi-proximal alternating direction method of multipliers to deal with it. The efficiency of the proposed algorithms is demonstrated on the random test problems, whose weight matrix H are highly ill-conditioned or rank deficient.