整数扩展欧几里得矩阵序列的选择项算法的修正

Wang和Pan提出了一个计算整数扩展欧几里得矩阵序列的选择项的算法,并把此算法应用于模有理数重构问题和数值有理数重构问题.这个算法仅消耗接近线性的时间复杂度,与目前已知的整数gcd算法的最佳时间复杂度相一致,而整数gcd算法只是此算法的一个特殊情形.分析了这个算法,指出了算法中由于考虑的不够全面而存在的错误,补充了矩阵序列性质的理论部分,并修正这个算法.     

求置换因子循环矩阵的逆阵及广义逆阵的快速算法

1 引 言 循环矩阵由于其应用非常广泛而成为一类重要的特殊矩阵,如在图象处理、编码理论、自回归滤波器设计等领域中经常会遇到以这类矩阵为系数的线性系统的求解问题.而对称循环组合系统也具有广泛的实际背景,例如造纸机的横向控制系统,具有平行结     

并行准高斯高阶递归滤波算法研究

三维变分同化系统中一个重要的问题是背景误差协方差矩阵B及其逆的求解.背景误差协方差矩阵的水平变换部分采用递归滤波运算,可以简化矩阵的求解,解决了背景误差协方差矩阵B及其逆难以求解的问题.本文对准高斯高阶递归滤波的算法原理和过程进行了深入研究.因为递归滤波并行的低可扩展性制约了高阶递归滤波算法在三维变分同化系统中的应用,所以本文提出了阶段二维区域剖分并行化方法,实现了并行准高斯高阶递归滤波算法库.数值试验表明,四阶递归滤波1次的效果明显优于一阶4次的滤波效果;并且高阶递归滤波并行算法64核时能达到大约50倍的加速,并行效率高达78%,具有良好的加速效果和较强的可扩展性.     

Verified error bounds for eigenvalues of geometric multiplicity <Emphasis Type="Italic">q</Emphasis> and corresponding invariant subspaces

In this paper, we generalize the algorithm described by Rump and Graillat to compute verified and narrow error bounds such that a slightly perturbed matrix is guaranteed to have an eigenvalue with geometric multiplicity q within computed error bounds. The corresponding invariant subspace can be directly obtained by our algorithm. Our verification method is based on border matrix technique. We demonstrate the performance of our algorithm for matrices of dimension up to hundreds with non-defective and defective eigenvalues.     

用随机奇异值分解算法求解矩阵恢复问题

本文研究了大型低秩矩阵恢复问题.利用随机奇异值分解（RSVD）算法,对稀疏矩阵做奇异值分解.该算法与Lanczos方法相比,在误差精度一致的同时运算时间大大降低,且该算法对相对低秩矩阵也有效.     

Roundoff Error Estimates of the Modified Gram–Schmidt Algorithm with Column Pivoting

In this paper we provide backward and forward roundoff error estimates of the modified Gram–Schmidt algorithm with column pivoting. It turns out that the row-wise growth factors of this algorithm are bounded. Furthermore, if the coefficient matrix is well conditioned, then with properly chosen tolerance , this algorithm can also correctly determine the numerical rank of the coefficient matrix. We also derive a forward roundoff error estimate of this algorithm for the solution of the least squares problem.     

三维电阻抗成像的体积元方法的数值模拟和分析

电阻抗成像是一类椭圆方程反问题,本文在三维区域上对其进行数值模拟和分析.对于椭圆方程Neumann边值正问题,本文提出了四面体单元上的一类对称体积元格式,并证明了格式的半正定性及解的存在性;引入单元形状矩阵的概念,简化了系数矩阵的计算;提出了对电阻率进行拼接逼近的方法来降低反问题求解规模,使之与正问题的求解规模相匹配;导出了误差泛函的Jacobi矩阵的计算公式,利用体积元格式的对称性和特殊的电流基向量,将每次迭代中需要求解的正问题的个数降到最低.一系列数值实验的结果验证了数学模型的可靠性和算法的可行性.本文所提出的这些方法,已成功应用于三维电阻抗成像的实际数值模拟.     

STABLE DOUBLE LR ALGORITHM AND ITS ERROR ANALYSIS

In this paper, the normative matrices and their double LR transformation with origin shifts are defined, and the essential relationship between the double LR transformation of a normative matrix and the QR transformation of the related symmetric tridiagonal matrix is proved. We obtain a stable double LR algorithm for double LR transformation of normative matrices and give the error analysis of our algorithm. The operation number of the stable double LR algorithm for normative matrices is only four sevenths of the rational QR algorithm for reed symmetric tridiagonal matrices.     

Approximation of the linear combination of $\varphi$-functions using the block shift-and-invert Krylov subspace method

In this paper, we develop an algorithm in which the block shift-and-invert Krylov subspace method can be employed for approximating the linear combination of the matrix exponential and related exponential-type functions. Such evaluation plays a major role in a class of numerical methods known as exponential integrators. We derive a low-dimensional matrix exponential to approximate the objective function based on the block shift-and-invert Krylov subspace methods. We obtain the error expansion of the approximation, and show that the variants of its first term can be used as reliable a posteriori error estimates and correctors. Numerical experiments illustrate that the error estimates are efficient and the proposed algorithm is worthy of further study.     

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.     

Robustness and applicability of Markov chain Monte Carlo algorithms for eigenvalue problems

In this paper we analyse applicability and robustness of Markov chain Monte Carlo algorithms for eigenvalue problems. We restrict our consideration to real symmetric matrices.

Almost Optimal Monte Carlo (MAO) algorithms for solving eigenvalue problems are formulated. Results for the structure of both – systematic and probability error are presented. It is shown that the values of both errors can be controlled independently by different algorithmic parameters. The results present how the systematic error depends on the matrix spectrum. The analysis of the probability error is presented. It shows that the close (in some sense) the matrix under consideration is to the stochastic matrix the smaller is this error. Sufficient conditions for constructing robust and interpolation Monte Carlo algorithms are obtained. For stochastic matrices an interpolation Monte Carlo algorithm is constructed.

A number of numerical tests for large symmetric dense matrices are performed in order to study experimentally the dependence of the systematic error from the structure of matrix spectrum. We also study how the probability error depends on the balancing of the matrix.     

多元积分方程自适应解法的最优化

In this paper it was considered that problem of optimization of adaptive direct algorithm of approximate solution of integral equations. For the Fredholm integral equations of second kind with kernels belonging to Besov classes there is determined the exact order of the error of an optimal adaptive direct algorithm and a algorithm for realizing it is indicated.     

SOME PROPERTIES OF CENTROSYMMETRIC MATRICES AND ITS APPLICATIONS

In this paper, some properties of centrosymmetric matrices, which often appear in the construction of orthonormal wavelet basis in wavelet analysis, are investigated. As an application, an algorithm which is tightly related to a so-called Lawton matrix is presented. In this algorithm, about only half of memory units are required and quarter of computational cost is needed by exploiting the property of the Lawton matrix and using a compression technique, it is compared to one for the original Lawton matrix.     

计算矩阵函数双线性形式的Krylov子空间算法的误差分析

矩阵函数的双线性形式u^Tf（A）v出现在很多应用问题中,其中u,v ∈ Rⁿ,A ∈ R^n×n,f（z）为给定的解析函数.开发其有效可靠的数值算法一直是近年来学术界所关注的问题,其中关于其数值算法的停机准则多种多样,但欠缺理论支持,可靠性存疑.本文将对矩阵函数的双线性形式u^Tf（A）v的数值算法和后验误差估计进行研究,给出其基于Krylov子空间算法的误差分析,导出相应的误差展开式,证明误差展开式的首项是一个可靠的后验误差估计,据此可以为算法设计出可靠的停机准则.     

范德蒙型方程组最小二乘解的快速算法

在用多项式进行曲线拟合等实际问题中,需要求解以范德蒙型矩阵VT为系数阵的线性方程组VTx=b的最小二乘解.     

关于ARMA序列协方差矩阵的逆

本文用矩阵方法导出ＡＲＭＡ（ｐ，ｑ）序列协方差阵的逆的一种表达式，由它可以较快计算平方和函数及其偏导数，还可以求得初值为零的条件平方和函数的误差。     

缺初值估计的统计特性

<正> 设x_o和{ξ_k}不相关,期望为Ex_o,协方差阵为R. 用y_o,…,y_k对x_j,0≤j≤k的线性无偏最小方差估计x_j(k)及其估计误差协方差阵P_j(k)有熟知的递推公式.为了强调x_j(k),p_j(k)和Ex_o、R的依赖关系,把它们分别记为x_j(k,Ex_o,R),P_j(k,Ex_o,R). 在实际情况中,Ex_o和只往往是未知量,至少知道得不确切.因此,如果用某—n维矢量a取代Ex_o,用某-n×n非负定Hermite阵R′取代R,那么一般说x_j(k,a,R′)不     

一类非线性矩阵方程对称解的双迭代算法

利用逆矩阵的Neumann级数形式,将在Schur插值问题中遇到的含未知矩阵二次项之逆的非线性矩阵方程转化为高次多项式矩阵方程,然后采用牛顿算法求高次多项式矩阵方程的对称解,并采用修正共轭梯度法求由牛顿算法每一步迭代计算导出的线性矩阵方程的对称解或者对称最小二乘解,建立求非线性矩阵方程的对称解的双迭代算法.双迭代算法仅要求非线性矩阵方程有对称解,不要求它的对称解唯一,也不对它的系数矩阵做附加限定.数值算例表明,双迭代算法是有效的.     

UZAWA ALGORITHM ON STABILIZED NAVIER STOKES PROBLEMS

In this paper, we consider the so-called "inexact Uzawa" algorithm applied to the unstable Navier-Stokes problem. We use stabilization matrix to stabilize the unstable system and proved theoretically that under given proper preconditioners, Uzawa algorithm is convergent for the stablization system. Bounds for the iteration error are provided. We show numerically that Uzawa algorithm is convergent as well for the sta     

On the applicability of Genocchi wavelet method for different kinds of fractional‐order differential equations with delay

A novel collocation method based on Genocchi wavelet is presented for the numerical solution of fractional differential equations and time‐fractional partial differential equations with delay. In this work, to achieve the approximate solution with height accuracy, we employed the operational matrix of integer derivative and the pseudo‐operational matrix of fractional derivative in Caputo sense. Also, based on Genocchi function properties, we presented delay and pantograph operational matrices of Genocchi wavelet functions (GWFs). Due to operational and pseudo‐operational matrices, the equations under this study can be turned into nonlinear algebraic equations with the unknown GWF coefficients. For illustrating the upper bound of error for the proposed method, we estimate the error in the sense of Sobolev space. In addition, to demonstrate the efficacy of the pseudo‐operational matrix of fractional derivative, we investigate the upper bound of error for the mentioned matrix. Finally, the algorithm based on the proposed approach is implemented for some numerical experiments to confirm accuracy and applicability.