带插值的自适应网格重构算法求解带移动热源的反应扩散方程的理论分析

本文研究一个带插值的网格重构算法求解一类带移动热源的反应扩散方程. 算法包括两步: 第一步是用旧时间网层上的计算解计算新时间层上的空间网格; 第二步是使用有限差分方法在新时间层 空间网格上离散方程, 并且将旧时间层上计算解的插值作为初始值. 对于时间, 我们获得了一阶收敛结果. 对于空间, 我们证明了使用线性插值算法的一阶收敛性和使用二次插值算法的二阶收敛性. 数值例子肯定了本文的理论结果.     

相对优集及其在不可约算法中的应用

从优集出发,提出了相对优集的定义及其计算算法.并将其应用到不可约零点分解中,提供了一种新的不可约零点分解算法.从实例计算结果可知,就某些多项式方程组而言,相对于原来已有的算法,使用相对优集修改后,能够很好地进行分解,减少了冗余分支的出现.     

一个求解非线性不等式约束优化问题的带有共轭梯度参数的广义梯度投影算法

本文提出一个求解非线性不等式约束优化问题的带有共轭梯度参数的广义梯度投影算法.算法中的共轭梯度参数是很容易得到的,且算法的初始点可以任意选取.而且,由于算法仅使用前一步搜索方向的信息,因而减少了计算量.在较弱条件下得到了算法的全局收敛性.数值结果表明算法是有效的.     

基于部分基变量的LP问题矩阵算法

基于部分基变量提出了LP问题的矩阵算法. 该算法以最优基矩阵的一个充分必要条件为基础,首先将一个初始矩阵转化为右端项和检验数均满足要求的矩阵,再转为检验数满足要求的基矩阵,最后转化为最优基矩阵.该算法具有使用范围广、计算规模小、计算过程简化、计算机易于实现的优势.矩阵算法的核心运算是求逆矩阵的运算,提出了矩阵算法的求逆问题,讨论并给出了求逆快速算法,该算法充分利用了矩阵算法迭代过程中提供的原来的逆矩阵的信息经过简单的变换得到新的逆矩阵,该算法比直接求逆法计算效率更高.     

多介质流体界面的守恒型跟踪法

本文中,我们对茅德康在【D.K.Mao,Towards front-tracking based on conservation in two space dimensionsⅡ,tracking discontinuities in capturing fashion,J.Comput.Phys.,226,(2007),pp 1550-1588】一文中所建立的守恒型跟踪法进行了改进,成功将算法运用到多介质流体界面的计算中.最后,我们使用改进后的算法计算了两个数值算例,验证了算法的有效性.     

基于Taylor级数的矩阵双曲余弦函数的数值算法

提出了一种基于Taylor级数的矩阵双曲余弦函数的数值逼近算法,为减少计算量使用了Paterson-Stockmeyer方法来计算矩阵Taylor多项式,对逼近误差进行了绝对后向误差分析以减少误差,并设计了算法可以较为快速且准确地求解矩阵双曲余弦函数,最后进行了数值实验,验证了算法的有效性.     

Euclid算法、Guass消元法以及Buchberger算法研究[英文]

本文给出计算多个正整数的最大公因子的算法,该算法是Euclid算法的推广,基于该算法可再次发现Guass消元法,而且不必使用多元除算法来简化Buchberger算法.     

一种寻找星图光斑质心的高精度算法及在成像畸变矫正中的应用

首先讨论星图识别中的质心寻找问题,提出了一种改进的匹配算法.使用高斯分布对光斑内像素点的强度分布进行近似模拟, 并采用最小二乘法中的法方程法对光斑图像质心坐标进行优化计算.算例表明该算法可以得到更为精确的结果, 在噪声小于最大像素值的$5\%$时,质心坐标计算精度高于0.04个像素, 优于以往的匹配算法的结果.最后讨论了算法在望远镜光学成像畸变矫正中的应用, 设计了矫正算法, 并通过算例验证了算法的合理性.     

任意初始点下的广义梯度投影滤子算法

提出了一个任意初始点的广义梯度滤子方法. 该方法不使用罚函数以避免由此带来的缺陷并可以减少计算量. 方法的另一个特点是不因使用了滤子技术而使算法早熟或陷入循环. 算法对初始点没有要求并在比较合理的条件下具有全局收敛性.     

实对称区间矩阵特征值确界的交错定理及其应用

本文将实对称矩阵特征值的交错定理推广到实对称区间矩阵,给出了实对称区间矩阵特征值确界的交错定理,并应用该定理构造了估计实对称三对角区间矩阵特征值界的算法.文中数值例子表明,本文所给算法与一些现有算法相比在使用范围、计算精度和计算量等方面都具有一定的优越性.     

Computing logarithms digit-by-digit

In this work, we present an algorithm for computing logarithms of positive real numbers, that bears structural resemblance to the elementary school algorithm of long division. Using this algorithm, we can compute successive digits of a logarithm using a 4-operation pocket calculator. The algorithm makes no use of Taylor series or calculus, but rather exploits properties of the radix-d representation of a logarithm in base d. As such, the algorithm is accessible to anyone familiar with the elementary properties of exponents and logarithms.     

Computing border bases

This paper presents several algorithms that compute border bases of a zero-dimensional ideal. The first relates to the FGLM algorithm as it uses a linear basis transformation. In particular, it is able to compute border bases that do not contain a reduced Gröbner basis. The second algorithm is based on a generic algorithm by Bernard Mourrain originally designed for computing an ideal basis that need not be a border basis. Our fully detailed algorithm computes a border basis of a zero-dimensional ideal from a given set of generators. To obtain concrete instructions we appeal to a degree-compatible term ordering σ and hence compute a border basis that contains the reduced σ-Gröbner basis. We show an example in which this computation actually has advantages over Buchberger's algorithm. Moreover, we formulate and prove two optimizations of the Border Basis Algorithm which reduce the dimensions of the linear algebra subproblems.     

Computing mountain passes and transition states

The mountain-pass theorem guarantees the existence of a critical point on a path that connects two points separated by a sufficiently high barrier. We propose the elastic string algorithm for computing mountain passes in finite-dimensional problems and analyze the convergence properties and numerical performance of this algorithm for benchmark problems in chemistry and discretizations of infinite-dimensional variational problems. We show that any limit point of the elastic string algorithm is a path that crosses a critical point at which the Hessian matrix is not positive definite.This work was supported by the Mathematical, Information, and Computational Sciences Division subprogram of the Office of Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy, under Contract W-31-109-Eng-38.     

Computing the complete CS decomposition

An algorithm for computing the complete CS decomposition of a partitioned unitary matrix is developed. Although the existence of the CS decomposition (CSD) has been recognized since 1977, prior algorithms compute only a reduced version. This reduced version, which might be called a 2-by-1 CSD, is equivalent to two simultaneous singular value decompositions. The algorithm presented in this article computes the complete 2-by-2 CSD, which requires the simultaneous diagonalization of all four blocks of a unitary matrix partitioned into a 2-by-2 block structure. The algorithm appears to be the only fully specified algorithm available. The computation occurs in two phases. In the first phase, the unitary matrix is reduced to bidiagonal block form, as described by Sutton and Edelman. In the second phase, the blocks are simultaneously diagonalized using techniques from bidiagonal SVD algorithms of Golub, Kahan, Reinsch, and Demmel. The algorithm has a number of desirable numerical features.      

Computing iterative roots of polygonal functions

Based on the iterative root theory for monotone functions, an algorithm for computing polygonal iterative roots of increasing polygonal functions was given by J. Kobza. In this paper we not only give an algorithm for roots of decreasing polygonal functions but also generalize Kobza's results to the general n. Furthermore, we extend our algorithms for polygonal PM functions, a class of non-monotonic functions.     

Computing hyperbolic choreographies

An algorithm is presented for numerical computation of choreographies in spaces of constant negative curvature in a hyperbolic cotangent potential, extending the ideas given in a companion paper [14] for computing choreographies in the plane in a Newtonian potential and on a sphere in a cotangent potential. Following an idea of Diacu, Pérez-Chavela and Reyes Victoria [9], we apply stereographic projection and study the problem in the Poincaré disk. Using approximation by trigonometric polynomials and optimization methods with exact gradient and exact Hessian matrix, we find new choreographies, hyperbolic analogues of the ones presented in [14]. The algorithm proceeds in two phases: first BFGS quasi-Newton iteration to get close to a solution, then Newton iteration for high accuracy.     

Computing the minimal covering set

We present the first polynomial-time algorithm for computing the minimal covering set of a (weak) tournament. The algorithm draws upon a linear programming formulation of a subset of the minimal covering set known as the essential set. On the other hand, we show that no efficient algorithm exists for two variants of the minimal covering set–the minimal upward covering set and the minimal downward covering set–unless P equals NP. Finally, we observe a strong relationship between von Neumann–Morgenstern stable sets and upward covering on the one hand, and the Banks set and downward covering on the other.     

Computing integral solutions of complementarity problems

In this paper an algorithm is proposed to find an integral solution of (nonlinear) complementarity problems. The algorithm starts with a nonnegative integral point and generates a unique sequence of adjacent integral simplices of varying dimension. Conditions are stated under which the algorithm terminates with a simplex, one of whose vertices is an integral solution of the complementarity problem under consideration.     

Computing the Matrix Cosine

An algorithm is developed for computing the matrix cosine, building on a proposal of Serbin and Blalock. The algorithm scales the matrix by a power of 2 to make the -norm less than or equal to 1, evaluates a Padé approximant, and then uses the double angle formula cos(2A)=2cos(A)²–I to recover the cosine of the original matrix. In addition, argument reduction and balancing is used initially to decrease the norm. We give truncation and rounding error analyses to show that an [8,8] Padé approximant produces the cosine of the scaled matrix correct to machine accuracy in IEEE double precision arithmetic, and we show that this Padé approximant can be more efficiently evaluated than a corresponding Taylor series approximation. We also provide error analysis to bound the propagation of errors in the double angle recurrence. Numerical experiments show that our algorithm is competitive in accuracy with the Schur–Parlett method of Davies and Higham, which is designed for general matrix functions, and it is substantially less expensive than that method for matrices of -norm of order 1. The dominant computational kernels in the algorithm are matrix multiplication and solution of a linear system with multiple right-hand sides, so the algorithm is well suited to modern computer architectures.