基于泰勒级数展开的一点超前差分公式的推导

传统的数值微分公式有前向差分、后向差分和中心差分公式.所谓一点超前差分公式,就是后向差分公式在形式上"前移"一点来计算一阶导数的公式.该公式有效地弥补了传统差分公式的不足之处.不同于以前研究中使用拉格朗日公式来推导一点超前公式的做法,给出了基于泰勒级数展开的对该组公式及其截断误差的推导,从另一个角度验证了一点超前公式,使其更为完善.     

基于前向差分的一阶数值微分公式验证与实践

根据多项式插值理论,可以通过构造相应的插值多项式来逼近未知的目标函数,再进一步求一阶导数,从而得到该目标函数的一阶数值微分公式.对于此数值微分公式,探讨基于前向差分的未知目标函数的多点一阶微分近似公式;即,等间距情况下的二至十六个数据点的前向差分公式.计算机数值实验进一步验证与表明,该用于未知目标函数一阶数值微分的多点公式可以取得较高的计算精度.     

二维分数阶发展型方程的正式的二阶BDF交替方向隐式紧致差分格式

该文将研究二维分数阶发展型方程的正式的二阶向后微分公式(BDF)的交替方向隐式(ADI)紧致差分格式.在时间方向上用二阶向后微分公式离散一阶时间导数,积分项用二阶卷积求积公式近似,在空间方向上用四阶精度的紧致差分离散二阶空间导数得到全离散紧致差分格式.基于与卷积求积相对应的实二次型的非负性,利用能量方法研究了差分格式的稳定性和收敛性,理论结果表明紧致差分格式的收敛阶为O(k~(a+1)+h_1~4+h_2~4),其中k为时间步长,h_1和h_2分别是空间x和y方向的步长.最后,数值算例验证了理论分析的正确性.     

一类非线性偏积分微分方程二阶差分全离散格式

给出了数值求解一类非线性偏积分微分方程的二阶全离散差分格式.采用了二阶向后差分格式,积分项的离散利用了Lubich的二阶卷积求积公式,给出了稳定性的证明、误差估计及收敛性的结果.     

基于分数阶差分的ARFIMA模型及预测效果研究

采用MRS分析法对香港恒生指数周数据序列的长期记忆性进行研究,并建立ARFIMA模型,推导了分数阶差分的计算过程。对分数阶差分的ARFIMA模型与一阶差分的ARFIMA模型进行了比较,发现应进行分数阶差分的序列,简化成一阶差分后,就有可能丢失许多有价值的信息,导致建模误差增大。进一步使用ARFIMA模型预测公式进行预测,结果显示ARFIMA模型预测效果不理想。在对香港恒生指数周数据进行预测时,ARFIMA模型几乎是失效的,并从两个不同的角度论证了这一结果出现的必然性。     

对论文"任意精度的三点紧致显格式及其在CFD中的应用"的评论

证明了林建国等(林建国,谢志华,周俊陶,任意精度的三点紧致显格式及其在CFD中的应用.应用数学和力学,2007,28(7):843-852)提出的紧致显格式与传统的差分格式实质相同,是传统差分格式的另一表达形式,并不具有紧致格式的优点.尽管如此,但这种表达形式更紧凑,推导获得高精度的差分表达式相对于传统的Taylor展开求待定系数的方法也更加简单.     

金融资产定价的统一视角及其在风险管理中的应用

在"资本资产定价基本原理"的基础上,通过对于传统定价方法过程的分析和总结,推导了金融资产定价的统一公式,并指明了效用理论中关于人的效用的刻画可以通过该公式中的权重系数体现出来,构成结合了效用理论和个体差异的"金融资产定价的统一视角";针对这一"统一视角",该文举出一例,将其应用于个人投资股票市场风险管理的实践中.     

一类偏积分微分方程一阶差分全离散格式

本文给出了数值求解一类偏积分微分方程的一阶差分全离散格式。时间方向采用了一阶向后差分格式，空间方向采用二阶差分格式，给出了稳定性的证明，误差估计及收敛性的结果，并给出了数值例子。     

一种求解Burgers方程的高精度紧致差分格式

针对Burgers方程,采用余项修正法和欧拉公式,推导了一种新的四层高精度紧致差分隐格式,其截断误差为O(τ~2+τh~2+h~4),即当τ=O(h~2)时,格式空间具有四阶精度;然后通过数值实验验证了格式的精确性和可靠性.     

高等数学视角下的弧微分公式推导及曲率公式适用条件

在利用弧微分公式推导曲率公式时,针对弧微分公式证明过程中“弧长和弦长的比值极限为1”假设不严谨的问题,本文在高等数学知识体系内,利用曲线直角坐标方程得到了弧长与有向弧段的值之间的关系,提出了一种证明弧微分公式的方法.之后,针对四种不同形式的曲线方程,推导并总结了不同方程下的曲率公式及其适用条件,并针对性地给出了两个典型例题.最后,给出了一个运用曲率公式求解实际工程问题的案例.     

The Deferred Correction Procedure for Linear Multistep Formulas

A general approach of deferred correction procedure based on linear multistep formulas is proposed. Several deferred correction procedures based on backward differentiation formulas, which allow us to develop L-stable algorithms of order up to 4 and $L(\alpha)$-stable algorithms of order up to 7, are derived. Preliminary numerical results indicate that this approach is indeed efficient.     

Implementation of chebyshevian linear multistep formulas

A Chebyshevian linear multistep formula is a formula fitted to a Chebyshev set of basis functions. This paper presents a unified approach for the implementation of Chebyshevian backward differentiation and Adams formulas for solving ordinary differential equations. The approach is based on generalized scaled differences, derived from generalized divided differences, and it includes the generalized Newton interpolation formula as predictor for the Chebyshevian implicit backward differentiation formula and Chebyshevian Adams-Bashforth-Moulton formulas. The local truncation errors are estimated by means of the scaled differences providing information for the control of order and steplength.     

Backward differentiation type formulas for Volterra integral equations of the second kind

Summary Numerical integration formulas are discussed which are obtained by differentiation of the Volterra integral equation and by applying backward differentiation formulas to the resulting integro-differential equation. In particular, the stability of the method is investigated for a class of convolution kernels. The accuracy and stability behaviour of the method proposed in this paper is compared with that of (i) a block-implicit Runge-Kutta scheme, and (ii) the scheme obtained by applying directly a quadrature rule which is reducible to the backward differentiation formulas. The present method is particularly advantageous in the case of stiff Volterra integral equations.     

Numerical solution of the finite horizon stochastic linear quadratic control problem

The treatment of the stochastic linear quadratic optimal control problem with finite time horizon requires the solution of stochastic differential Riccati equations. We propose efficient numerical methods, which exploit the particular structure and can be applied for large‐scale systems. They are based on numerical methods for ordinary differential equations such as Rosenbrock methods, backward differentiation formulas, and splitting methods. The performance of our approach is tested in numerical experiments.     

High‐order characteristic‐tracking strategy for simulation of a nonlinear advection–diffusion equation

In this study, new high‐order backward semi‐Lagrangian methods are developed to solve nonlinear advection–diffusion type problems, which are realized using high‐order characteristic‐tracking strategies. The proposed characteristic‐tracking strategies are second‐order L‐stable and third‐order L(α)‐stable methods, which are based on a classical implicit multistep method combined with a error‐correction method. We also use backward differentiation formulas and the fourth‐order finite‐difference scheme for diffusion problem discretization in the temporal and spatial domains, respectively. To demonstrate the adaptability and efficiency of these time‐discretization strategies, we apply these methods to nonlinear advection–diffusion type problems such as the viscous Burgers' equation. Through simulations, not only the temporal and spatial accuracies are numerically evaluated but also the proposed methods are shown to be superior to the compared existing characteristic‐tracking methods under the same rates of convergence in terms of accuracy and efficiency. Finally, we have shown that the proposed method well preserves the energy and mass when the viscosity coefficient becomes zero.     

The construction of high order convergent look-ahead finite difference formulas for Zhang Neural Networks

ABSTRACT

Zhang Neural Networks rely on convergent 1-step ahead finite difference formulas of which very few are known. Those which are known have been constructed in ad-hoc ways and suffer from low truncation error orders. This paper develops a constructive method to find convergent look-ahead finite difference schemes of higher truncation error orders. The method consists of seeding the free variables of a linear system comprised of Taylor expansion coefficients followed by a minimization algorithm for the maximal magnitude root of the formula's characteristic polynomial. This helps us find new convergent 1-step ahead finite difference formulas of any truncation error order. Once a polynomial has been found with roots inside the complex unit circle and no repeated roots on it, the associated look-ahead ZNN discretization formula is convergent and can be used for solving any discretized ZNN based model. Our method recreates and validates the few known convergent formulas, all of which have truncation error orders at most 4. It also creates new convergent 1-step ahead difference formulas with truncation error orders 5 through 8.     

Mathematical proof of closed form expressions for finite difference approximations based on Taylor series

Taylor series based finite difference approximations of derivatives of a function have already been presented in closed forms, with explicit formulas for their coefficients. However, those formulas were not derived mathematically and were based on observation of numerical results. In this paper, we provide a mathematical proof of those formulas by deriving them mathematically from the Taylor series.     

Some results on extremal vectors and invariant subspaces

In 1996 P. Enflo introduced the concept of extremal vectors and their connection to the Invariant Subspace Problem. The study of backward minimal vectors gives a new method of finding invariant subspaces which is more constructive than the previously known methods. In this article we study the properties and behaviour of extremal vectors, give some new formulas related to backward minimal vectors and improve results from papers by Ansari and Enflo (1998) and Enflo (1998).

     

Methods for parallel integration of stiff systems of odes

This paper presents a class of parallel numerical integration methods for stiff systems of ordinary differential equations which can be partitioned into loosely coupled sub-systems. The formulas are called decoupled backward differentiation formulas, and they are derived from the classical formulas by restricting the implicit part to the diagnonal sub-system. With one or several sub-systems allocated to each processor, information only has to be exchanged after completion of a step but not during the solution of the nonlinear algebraic equations.The main emphasis is on the formula of order 1, the decoupled implicit Euler formula. It is proved that this formula even for a wide range of multirate formulations has an asymptotic global error expansion permitting extrapolation. Besides, sufficient conditions for absolute stability are presented.     

An unstructured mesh finite volume method for modelling saltwater intrusion into coastal aquifers

In this paper, a two-dimensional finite volume unstructured mesh method (FVUM) based on a triangular background interpolation mesh is developed for analysing the evolution of the saltwater intrusion into single and multiple coastal aquifer systems. The model formulation consists of a ground-water flow equation and a salt transport equation. These coupled and non-linear partial differential equations are transformed by FVUM into a system of differential/algebraic equations, which is solved using backward differentiation formulas of order one through five. Simulation results are compared with previously published solutions where good agreement is observed.