最佳等参元

等参元及其参数变换的插值方法。是有限元分析的有力工具之一,在工程计算中,得到广泛的应用. 在有限元分析中,当采用等参元时,一旦单元的等参坐标变换的Jacobi矩阵发生奇异,就要中止计算,下机修改原有的单元剖分,直到所有单元的Jacobi矩阵均非奇异. [1]突破原等参元的规定,给出了八节点Serendipity等参元的修改公式;[2]也给出了类似的修改公式.上述均以数值例子说明新公式的优点.而[3—6]完整、系统地给出     

一种求二元有理插值函数的方法

给出一种方法可直接计算基于矩形节点的二元有理插值函数的分母在节点处的值 ,进而判断相应的二元有理插值函数是否存在 .此方法运用灵活 ,适用范围广 ,在相应的有理插值函数存在时 ,能给出它的具体表达式 .此外 ,我们还针对文中两个主要逆矩阵 ,给出了相应的递推公式 ,避免了求逆计算 .     

Jacobi椭圆函数有理式的Fourier级数*

本文列出了手册[1]及文献[2]中未计算过的九十余个Jacobi椭圆函数sn(u,k),cn(u,k),dn(u,k)的有理函数的Fourier展式.对于用Melnikov方法研究可积系统在周期扰动下的次谐波分枝与浑沌性质,及其他工程物理中的计算问题,这些公式可供查阅应用.     

二元矩阵有理插值函数的构造

一般构造矩阵值有理函数的方法是利用连分式给出的,其算法的可行性不易预知,且计算量大.本文对于二元矩阵值有理插值的计算,通过引入多个参数,定义一对二元多项式:代数多项式和矩阵多项式,利用两多项式相等的充分必要条件通过求解线性方程组确定参数,并由此给出了矩阵值有理插值公式.该公式简单,具有广阔的应用前景.     

一种有理插值型求积公式的收敛性

构造一种有理插值型求积公式,证明其收敛性,并给出数值计算实例.该方法推广了Sloan和Smith等人的结果.     

Thiele重心型矩阵值混合有理插值算法

利用Samelson型矩阵广义逆,构造了一种基于Thiele型连分式插值与重心有理插值的相结合的二元矩阵值混合有理插值格式,这种新的混合矩阵值有理插值函数继承了连分式插值和重心插值的优点,它的表达式简单,计算方便,数值稳定性好.该算法满足有理插值问题所给的插值条件,同时给出了误差估计分析.最后用数值算例验证了插值算法的有效性.     

基于连分式与Newton-Padé逼近的数值积分

首先利用Newton-Pade表中部分序列推导出连分式,提出逆差商算法,算出关于高阶导数与高阶差商的连分式插值余项.接着,构造基于此类连分式的有理求积公式与相应的复化求积公式,算出相应的求积余项,研究表明,在一定条件下,求积公式序列一致收敛于积分真值.然后,为保证连分式计算顺利进行,研究连分式分母非0的充分条件.最后,若干数值算例表明,对某些函数采用新提出的复化有理求积公式计算数值积分,所得结果优于采用Simpson公式.     

非线性Klein-Gordon方程的广义Jacobi谱配置方法

构造非线性Klein-Gordon方程的广义Jacobi谱配置格式,并给出相应收敛性分析.文中的方法和技巧为设计和分析各类线性与非线性偏微分方程的谱配置格式提供了有效的框架.     

一类线性隐式A稳定的单步法

1.引言 对于Stiff方程组初值问题的数值解法,Dahlquist在[1]中引进了 A稳定的概念,并且证明了显式的线性多步法(包括显式的Runge-Kutta方法)不可能是A稳定的.现在已经有许许多多隐式A稳定或Stiff稳定的方法,但绝大多数在数值解的过程中必须解由于隐式方法所产生的非线性方程组,而非线性方程组的求解过程往往又要采用Newton-Raphson迭代方法,因此需要计算方程y’=f(x,y)的右函数f(x,y)的Jacobi矩阵以及与此有关的逆矩阵.本文的主要思想是:既然在数值解过程中要计算f(x,y)的Jacobi矩阵,那么不妨在数值公式中明显的出现f(x,y)的一阶偏导数.我们将A稳定公式     

有理圆锥曲线段的参数的几何意义

用代数和几何方法, 得到用有理二次或有理三次Bézier曲线表示的圆锥曲线上的点与其参数域上的点所对应的函数关系; 即给出了有理圆锥曲线段的表达式所描述的映射的逆映射公式．这种公式用圆锥曲线段上此点和控制顶点所决定的三角形面积、角度及有理Bézier曲线的权因子来表示, 或用此点和曲线段首末端点相应的参数角度及有理Bézier曲线的权因子来表示. 这些结果对有理Bézier曲线曲面的最佳参数化和重新参数化等算法实现是极其有益的.     

On the spectral radius of the Jacobi iteration matrix for a rectangular region with two different media

The spectral radius of the Jacobi iteration matrix plays an important role to estimate the optimum relaxation factor, when the successive overrelaxation (SOR) method is used for solving a linear system. The specific systems are finite difference forms of the Laplace equation satisfied on a rectanglar region with two different media. Though the potential function for the inhomogeneous closed region is continuous, the first order derivative is not continuous. So this requires internal boundary conditions or interface conditions. In this paper, the spectral radius of the Jacobi iteration matrix for the inhomogeneous rectangular region is formulated and the approximation for the explicit formula, suitable for the computation of the spectral radius, is deduced. It is also found by the proposed formula that the spectral radius and the optimum relaxation factor rigorously depend on the inhomogeneity or the internal boundary conditions in the closed region, and especially vary with the position of the internal boundary. These findings are also confirmed by the numerical results of the power method.The stationary iterative method using the proposed formula for calculating estimates of the spectral radius of the Jacobi iteration matrix is compared with Carré's method, Kulstrud's method and the stationary iterative method using Frankel's theoretical formula, all for the case of some numerical models with two different media. According to the results our stationary iterative method gives the best results ffor the estimate of the spectral radius of the Jacobi iteration matrix, for the required number of iterations to calculate solutions, and for the accuracy of the solutions.As a numerical example the microstrip transmission line is taken, the propating mode of which can be approximated by a TEM mode. The cross section includes inhomogeneous media and a strip conductor. Upper and lower bounds of the spectral radius of the Jacobi iteration matrix are estimated. Our method using these estimates is also compared with the other methods. The upper bound of the spectral radius of the Jacobi iteration matrix for more general closed regions with two different media might be given by the proposed formula.     

Mathematical stencil and its application in finite difference approximation to the poisson equation

The concept of mathematical stencil and the strategy of stencil elimination for solving the finite difference equation is presented,and then a new type of the iteration algo- rithm is established for the Poisson equation.The new algorithm has not only the obvious property of parallelism,but also faster convergence rate than that of the classical Jacobi iteration.Numerical experiments show that the time for the new algorithm is less than that of Jacobi and Gauss-Seidel methods to obtain the same precision,and the computational velocity increases obviously when the new iterative method,instead of Jacobi method,is applied to polish operation in multi-grid method,furthermore,the polynomial acceleration method is still applicable to the new iterative method.     

Jacobi rational approximation and spectral method for differential equations of degenerate type

We introduce an orthogonal system on the half line, induced by Jacobi polynomials. Some results on the Jacobi rational approximation are established, which play important roles in designing and analyzing the Jacobi rational spectral method for various differential equations, with the coefficients degenerating at certain points and growing up at infinity. The Jacobi rational spectral method is proposed for a model problem appearing frequently in finance. Its convergence is proved. Numerical results demonstrate the efficiency of this new approach.

     

Rational Jacobi elliptic solutions for nonlinear differential–difference lattice equations

In this work, we present a direct new method for constructing the rational Jacobi elliptic solutions for nonlinear differential–difference equations, which may be called the rational Jacobi elliptic function method. We use the rational Jacobi elliptic function method to construct many new exact solutions for some nonlinear differential–difference equations in mathematical physics via the lattice equation. The proposed method is more effective and powerful for obtaining the exact solutions for nonlinear differential–difference equations.     

Structured eigenvalue problems for rational gauss quadrature

The connection between Gauss quadrature rules and the algebraic eigenvalue problem for a Jacobi matrix was first exploited in the now classical paper by Golub and Welsch (Math. Comput. 23(106), 221–230, 1969). From then on many computational problems arising in the construction of (polynomial) Gauss quadrature formulas have been reduced to solving direct and inverse eigenvalue problems for symmetric tridiagonals. Over the last few years (rational) generalizations of the classical Gauss quadrature formulas have been studied, i.e., formulas integrating exactly in spaces of rational functions. This paper wants to illustrate that stable and efficient procedures based on structured numerical linear algebra techniques can also be devised for the solution of the eigenvalue problems arising in the field of rational Gauss quadrature.     

病态线性方程组新的Jacobi迭代解法

给出了解病态线性方程组的一种新的Jacobi迭代算法,并证明了算法的收敛性;通过具体算例说明了算法的实用性和有效性.     

应用迭代法求解一类非线性问题

本文应用迭代法求解一类有限维非线性问题,该方法是求解线性问题的雅可比迭代法在非线性问题上的推广,且此迭代方法具有几何收敛性质.     

A new Jacobi rational–Gauss collocation method for numerical solution of generalized pantograph equations

This paper is concerned with a generalization of a functional differential equation known as the pantograph equation which contains a linear functional argument. In this article, a new spectral collocation method is applied to solve the generalized pantograph equation with variable coefficients on a semi-infinite domain. This method is based on Jacobi rational functions and Gauss quadrature integration. The Jacobi rational-Gauss method reduces solving the generalized pantograph equation to a system of algebraic equations. Reasonable numerical results are obtained by selecting few Jacobi rational–Gauss collocation points. The proposed Jacobi rational–Gauss method is favorably compared with other methods. Numerical results demonstrate its accuracy, efficiency, and versatility on the half-line.     

Convergence theory of extrapolated iterative methods for a certain class of non-symmetric linear systems

Summary A variety of iterative methods considered in [3] are applied to linear algebraic systems of the formAu=b, where the matrixA is consistently ordered [12] and the iteration matrix of the Jacobi method is skew-symmetric. The related theory of convergence is developed and the optimum values of the involved parameters for each considered scheme are determined. It reveals that under the aforementioned assumptions the Extrapolated Successive Underrelaxation method attains a rate of convergence which is clearly superior over the Successive Underrelaxation method [5] when the Jacobi iteration matrix is non-singular.     

Jacobi-Picard iteration method for the numerical solution of nonlinear initial value problems

In this paper, an effective numerical iterative method for solving nonlinear initial value problems (IVPs) is presented. The proposed iterative scheme, called the Jacobi-Picard iteration (JPI) method, is based on the Picard iteration technique, orthogonal shifted Jacobi polynomials, and shifted Jacobi-Gauss quadrature formula. In comparison with traditional methods, the JPI method uses an iterative formula for updating next step approximations and calculating integrals of the shifted Jacobi polynomials are performed via an exact relation. Also, a vector-matrix form of the JPI method is provided in details which reduce the CPU time. The performance of the presented method has been investigated by solving several nonlinear IVPs. Numerical results show the efficiency and the accuracy of the proposed iterative method.