求解第一类积分方程的正则化—小波方法及其数值试验

1 方法的描述 第一类(Fredholm)积分方程是指形如 (1.1)的积分方程,其中核k(x,y)和右端函数f(x)给定,u(x)是未知函数.许多物理、化学、力学和工程应用问题都能导致第一类积分方程.求解第一类积分方程的一个本质性困难是方程的不适定性,即解的存在性、唯一性和稳定性遭到破坏.常用的数值方法有奇异值分解(SVD)方法、Tikhonov正则化方法、投影方法、正则化-样条方法、再生核方法等.本文提出一种新的正则化-小波方法,在第一类积分方程有多个解时,可以求出具有最小范数的数值解;如果原积分方程有唯一解,则所得的数值解收敛于准确解.数值试验表明,该方法是可行的. 我们在L~2[a,b]中考虑第一类(Fredholm)积分方程,即假设方程(1.1)中积分算子K∈L~2([a,b]×[a,b])及右端f(x)∈L~2[a,b]给定.为保证数值求解算法的稳定性,我们先用正则化方法处理该方程,将不适定问题化为泛函极值问题来求解,然后利用多重正交样条小波基构造求解格式.由于我们给出了直接计算低阶的多重正交样条小波基函数的一般公式,使得解法可以在计算机迅速实现.     

线性随机延迟积分微分方程Euler-Maruyama方法的稳定性

本文研究一类线性随机延迟积分微分方程Euler-Maruyama方法的MS-稳定性.首先,我们讨论方程真解的均方指数稳定性条件.然后,在此假设条件下,证明了带有复合梯形公式的Euler-Maruyama方法是MS-稳定的.最后,数值试验验证了本文的结论.     

高阶非完整系统运动方程的一类积分

本文给出高阶非完整系统运动方程的一类积分及其存在条件,包括1阶积分(广义能量积分),2阶积分和p(p>2)阶积分,所有这些积分都可按系统的Lagrange函数来构造.举例说明本文方法的应用.     

海面下方多障碍体散射问题数值研究

本文针对二维空间中海面下方多障碍体散射问题,分别从理论分析和数值计算两方面进行研究.通过分析散射问题的特性,利用Helmholtz方程,结合不同边界条件以及无穷远处辐射条件,建立了海面下方多障碍体散射问题的数学模型,并证明了散射问题解的唯一性.基于位势理论,利用间接积分方程方法,得到了不同区域的场所满足的积分表示,以及边界上密度函数所满足的边界积分方程.通过引入位势算子,将积分区域进行截断,得到有界域上的算子方程.针对所建立的边界积分方程系统,利用Nystr?m方法构造数值格式,并证明了数值解的收敛性.最后,利用数值实验验证理论的正确性和有效性.进一步,通过设计数值实验分析不同参数对散射问题的影响.     

推广的KdV方程特征问题解的存在唯一性

推广的KdV方程u_t+αuu_x+μu_x3+εu_x5=0[1]是典型的可积方程.它先后在研究冷等离子体中磁声波的传播[2],传输线中孤立波[3]和分层流体中界面孤立波[4]时导出.本文对推广的KdV方程的特征问题,在Riemann函数的基础上,设计一恰当结构,并由此化待征问题为一与之等价的积分微分方程.而该积分微分方程对应的映射E是列自身的映射[5],依不动点原理,积分微分方程有唯一的正则解,即推广的KdV方程的特征问题有唯一解,且由积分微分方程序列所得的迭代解于Ω上一致收敛.     

分数积分的一种数值计算方法及其应用

提出了一种只需要存储部分历史数据的分数积分的数值计算方法,并给出了误差估计。这种方法可对包含分数积分和分数导数的积分-微分方程进行较长时间的数值计算,克服了存储全部历史数据的困难,并能对计算误差进行控制。作为应用,给出了具有分数导数型本构关系的粘弹性Timoshenko梁的动力学行为研究的控制方程,利用分离变量法讨论梁在简谐激励作用下的动力响应,然后用新提出的数值方法对控制方程进行数值计算,数值计算结果和理论结果进行了比较,它们比较吻合。     

一类Fredholm-Volterra型积分方程的数值求解

本文引入契贝晓夫多项式作为基函数,利用Galerkin方法研究了一类Fredholm-Volterra积分方程的数值解,并进行了数值模拟.结果表明,该方法可行且有效.     

二维RLW方程的Cauchy问题

通过椭圆积分求出了二维RLW方程椭圆余弦波解,并用先验估计方法证明了该方程Cauchy问题关于小x、y周期解的若干性质和解的唯一性、稳定性。     

一种基于积分方程的数值微分方法

本文研究了目前一些求解数值微分的方法无法求出端点导数或是求出的端点附近导数不可用的问题.利用构造一类积分方程的方法,将数值微分问题转化为这类积分方程的求解,并用一种加速的迭代正则化方法来求解积分方程. 数值实验结果表明该算法可以有效求出端点的导数,且具有数值稳定、计算简单等优点.     

求Abel型积分方程数值解的正则化方法

本文采用近似已知函数稳定求导方法与两点复合Gauss-Legendre求积公式相结合求Abel型积分方程数值解,其结果是数值稳定且精度较高.给出了数值例子.     

Stability in the Numerical Solution of Linear Parabolic Equations with a Delay Term

This paper is concerned with the stability of numerical processes that arise after semi-discretization of linear parabolic equations wit a delay term. These numerical processes are obtained by applying step-by-step methods to the resulting systems of ordinary delay differential equations. Under the assumption that the semi-discretization matrix is normal we establish upper bounds for the growth of errors in the numerical processes under consideration, and thus arrive at conclusions about their stability. More detailed upper bounds are obtained for -methods under the additional assumption that the eigenvalues of the semi-discretization matrix are real and negative. In particular, we derive contractivity properties in this case. Contractivity properties are also obtained for the -methods applied to the one-dimensional test equation with real coefficients and a delay term. Numerical experiments confirming the derived contractivity properties for parabolic equations with a delay term are presented.     

Numerical methods for nonlinear stochastic differential equations with jumps

We present and analyse two implicit methods for Ito stochastic differential equations (SDEs) with Poisson-driven jumps. The first method, SSBE, is a split-step extension of the backward Euler method. The second method, CSSBE, arises from the introduction of a compensated, martingale, form of the Poisson process. We show that both methods are amenable to rigorous analysis when a one-sided Lipschitz condition, rather than a more restrictive global Lipschitz condition, holds for the drift. Our analysis covers strong convergence and nonlinear stability. We prove that both methods give strong convergence when the drift coefficient is one-sided Lipschitz and the diffusion and jump coefficients are globally Lipschitz. On the way to proving these results, we show that a compensated form of the Euler–Maruyama method converges strongly when the SDE coefficients satisfy a local Lipschitz condition and the pth moment of the exact and numerical solution are bounded for some p>2. Under our assumptions, both SSBE and CSSBE give well-defined, unique solutions for sufficiently small stepsizes, and SSBE has the advantage that the restriction is independent of the jump intensity. We also study the ability of the methods to reproduce exponential mean-square stability in the case where the drift has a negative one-sided Lipschitz constant. This work extends the deterministic nonlinear stability theory in numerical analysis. We find that SSBE preserves stability under a stepsize constraint that is independent of the initial data. CSSBE satisfies an even stronger condition, and gives a generalization of B-stability. Finally, we specialize to a linear test problem and show that CSSBE has a natural extension of deterministic A-stability. The difference in stability properties of the SSBE and CSSBE methods emphasizes that the addition of a jump term has a significant effect that cannot be deduced directly from the non-jump literature.This work was supported by Engineering and Physical Sciences Research Council grant GR/T19100 and by a Research Fellowship from The Royal Society of Edinburgh/Scottish Executive Education and Lifelong Learning Department.     

A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise

In this paper a family of fully implicit Milstein methods are introduced for solving stiff stochastic differential equations (SDEs). It is proved that the methods are convergent with strong order 1.0 for a class of SDEs. For a linear scalar test equation with multiplicative noise terms, mean-square and almost sure asymptotic stability of the methods are also investigated. We combine analytical and numerical techniques to get insights into the stability properties. The fully implicit methods are shown to be superior to those of the corresponding semi-implicit methods in term of stability property. Finally, numerical results are reported to illustrate the convergence and stability results.     

Numerical Stability and Oscillations of Runge-Kutta Methods for Differential Equations with Piecewise Constant Arguments of Advanced Type

For differential equations with piecewise constant arguments of advanced type, numerical stability and oscillations of Runge-Kutta methods are investigated. The necessary and sufficient conditions under which the numerical stability region contains the analytic stability region are given. The conditions of oscillations for the Runge-Kutta methods are obtained also. We prove that the Runge-Kutta methods preserve the oscillations of the analytic solution. Moreover, the relationship between stability and oscillations is discussed. Several numerical examples which confirm the results of our analysis are presented.     

The composite Milstein methods for the numerical solution of Ito stochastic differential equations

In this paper, we present the composite Milstein methods for the strong solution of Ito stochastic differential equations. These methods are a combination of semi-implicit and implicit Milstein methods. We give a criterion for choosing either the implicit or the semi-implicit scheme at each step of our numerical solution. The stability and convergence properties are investigated and discussed for the linear test equation. The convergence properties for the nonlinear case are shown numerically to be the same as the linear case. The stability properties of the composite Milstein methods are found to be more superior compared to those of the Milstein, the Euler and even better than the composite Euler method. This superiority in stability makes the methods a better candidate for the solution of stiff SDEs.     

Exponential mean-square stability of the improved split-step theta methods for non-autonomous stochastic differential equations

We consider the mean-square stability of the so-called improved split-step theta method for stochastic differential equations. First, we study the mean-square stability of the method for linear test equations with real parameters. When θ 3/2, the improved split-step theta methods can reproduce the mean-square stability of the linear test equations for any step sizes h 0. Then, under a coupled condition on the drift and diffusion coefficients, we consider exponential mean-square stability of the method for nonlinear non-autonomous stochastic differential equations. Finally, the obtained results are supported by numerical experiments.     

General linear methods for Volterra integral equations

We investigate the class of general linear methods of order p and stage order q=p for the numerical solution of Volterra integral equations of the second kind. Construction of highly stable methods based on the Schur criterion is described and examples of methods of order one and two which have good stability properties with respect to the basic test equation and the convolution one are given.     

Special stability problems for functional differential equations

Stability properties of numerical methods for functional differential equations, similar to A-stability for ordinary differential equations, are considered. Definitions are proposed for categories of numerical stability. Some of the backward differentiation methods are shown to have these stability properties.     

Numerical approximation of a metastable system

Using the Becker-Döring cluster equations as an example,we highlight some of the problems that can arise in the numericalapproximation of dynamical systems with slowly varying solutions.We describe the Becker-Döring model, summarize some ofits properties and construct a numerical approximation whichallows accurate and efficient computation of solutions in thelong, slowly varying metastable phase. We use the approximationto obtain test results and discuss the clear relationship betweenthem and equilibrium solutions of the Becker-Döring equations.     

Numerical approximations and regularizations of Riccati equations arising in hyperbolic dynamics with unbounded control operators

This paper provides an approximation theory for numerical computations of the solutions to algebraic Riccati equations arising in hyperbolic, boundary control problems. One of the difficulties in the approximation theory for Riccati equations is that many attractive numerical methods (such as standard finite elements) do not satisfy a uniform stabilizability condition, which is necessary for the stability of the approximate Riccati solutions. To deal with these problems, a regularizationapproximation technique, based on the introduction of special artificial terms to the dynamics of the original model, is proposed. The need for this regularization appears to be a distinct feature of hyperbolic (hyperbolic-like) equations, rather than parabolic (parabolic-like) problems where the smoothing effect of the dynamics is beneficial for the convergence and stability properties of approximate solutions to the associated Riccati equations (see [14]). The ultimate result demonstrates that the regularized, finite-dimensional feedback control yields near optimal performance and that the corresponding Riccati solution satisfies all the desired convergence properties. The general theory is illustrated by an example of a boundary control problem associated with the Kirchoff plate model. Some numerical results are provided for the given example.