基于PDE模型的图像处理方法

介绍了异质扩散偏微分方程 ( PDE)和几何驱动 ( GD)图像处理新方法 .对照传统滤波方法 ,分析了PDE和 GD方法的优点 ,并给出用于模糊和噪声图像恢复处理的两个模型     

一类非线性对流扩散问题的FDSD预测校正格式

1．引言由Hughes和Brooks门提出,并经Johnson等人［‘－‘1发展的流线扩散法（Streamline－DiffusionMetho人以下简称SD方法）是求解对流占优扩散问题（包括纯双曲问题）的一种有效的数值方法．由于良好的数值稳定性及其高阶收敛率,SD方法已广泛地应用于计算流体等诸多科学工程计算．然而,传统的sD方法利用时一空有限元求解发展型问题,导致对高维问题工作量过于庞大;其编程实现较复杂,对非线性问题也不便进行线性化处理．为使SD方法能够较简便地应用于高维和非线性问题,孙撒问提出了仅对空间域作有限元离散,而对时间域作差分…     

图像恢复的一种快速迭代正则化方法

本文研究了将图像恢复问题转化为大型的线性不适定问题的求解.利用由Landweber迭代正则化方法改进所得到的快速收敛的迭代正则化方法,处理具有可分离点扩散函数的图像恢复问题.图像恢复实验表明该方法可大大提高收敛速度,且在计算中只需要较少的存储量.     

一类非线性方程解的存在和唯一性及在图像中的应用

本文我们给出一个修正的非线性扩散方程模型，与Cotte Lions和Morel的模型相比该模型有许多实质上的优点。主要的想法是把原来去噪声部分：卷积Gauss过程替代为解一个有界区域上的线性抛物方程问题，因此避开了对初始数值如何全平面延拓的问题。我们从数学上的证明该问题解的存在性和适定性，同时给出对矩形域情况的解的级数形式。最后我们给基于本模型的数值计算差分模型，并且给出几个具体图像在该模型下处理结果。     

二维圆盘传递装置药物非线性扩散的优化控制模型及算法

本文首先给出了二维圆盘传递装置在极坐标下的药物非线性扩散最优控制模型.然后,用基于迭代法的最小二乘方法求解模型的非线性扩散方程,并估计相应的扩散系数.最后,通过一个数值算例,验证该控制模型和算法在二维圆盘传递装置中是有效的.     

基于变分法对一类非线性扩散方程解析解研究北大核心CSCD

本文分别针对一类扩散系数为非线性指数函数和幂函数的扩散方程,基于变分原理中的泛函极值理论分别提出了求解该方程Dirichlet边界和Neumann边界问题解析解的新方法,并证明了新方法是泛函问题极值解的充要性．以非饱和土壤水分运动问题为背景,给出了积水和恒通量条件下水平吸渗问题的解析解,并通过数值算例将解析解与数值解进行了比较分析,结果表明本文方法得到的解析解能够准确预测非饱和土壤水分水平吸渗问题的土壤含水量分布,是一种有效方法．因此本文方法为求解这一类非线性扩散方程提供了一种有效的新方法．     

非线性对流扩散方程的三层隐-显hp-局部间断Galerkin有限元方法

使用Arnold等人提出的求解椭圆方程的间断有限元的一般框架及新的处理非线性对流项的方法,得到了非线性对流扩散方程的三层隐-显hp-LDG方法的误差估计.对Burgers方程进行了数值计算,计算结果验证了文中得到的理论结果.     

对流扩散方程一类改进的特征线修正有限元方法

１引言在地下水污染,地下渗流驱动,核污染,半导体等问题的数值模拟中,均涉及抛物型对流扩散方程（或方程组）的数值求解问题．这些对流扩散型偏微分方程（或方程组）具有共同的特点：对流的影响远大于扩散的影响,即对流占优性,对流占优性给问题的数值求解带来许多困难,因此对流占优问题的有效数值解法一直是计算数学中重要的研究内容．用通常的差分法或有限元法进行数值求解将出现数值振荡．为了克服数值振荡,提出各种迎风方法和修正的特征方法并在这些问题上得到成功的实际应用、８０年代,Ｄｏｕｇｌａｓ和Ｒｕｓｓｅｌｌ［２］等…     

二维非线性对流扩散方程特征有限元的两重网络算法

针对二维非线性对流扩散方程,构造了特征有限元两重网格算法．该算法只需要在粗网格上进行非线性迭代运算,而在所需要求解的细网格上进行一次线性运算即可．对于非线性对流占优扩散方程,不仅可以消除因对流占优项引起的数值振荡现象,还可以加快收敛速度、提高计算效率．误差估计表明只要选取粗细网格步长满足一定的关系式,就可以使两重网格解与有限元解保持同样的计算精度．算例显示:两重网格算法比特征有限元算法的收敛速度明显加快．     

对流扩散问题的交替方向特征有限元方法

1 引言 在对流扩散方程的数值方法研究中,近年来由Douglas等人提出一种特征线修正法,并广泛应用于油藏模拟问题,核废料污染问题,半导体器件瞬态问题等领域.采用这种方法处理对流为主扩散问题时可以在不降低计算精度的情况下提高计算效率.实际问题一般是多维的,无论是用有限元或是差分法进行数值解都要解高阶的代数方程组,计算是相当复杂的.因此,研究如何对多维问题进行降维处理的数值方法无疑有着很重要的理论和实际意义.由算子的近似分解理论导出的交替方向迭代法,即可以把多维问题化为一维问题迭代求解,具有存贮量少,计算效率高等优点.本文对矩形区域上的二维对流扩散方程     

Boosting the accuracy of finite difference schemes via optimal time step selection and non-iterative defect correction

In this article, we present a unified analysis of the simple technique for boosting the order of accuracy of finite difference schemes for time dependent partial differential equations (PDEs) by optimally selecting the time step used to advance the numerical solution and adding defect correction terms in a non-iterative manner. The power of the technique, which is applicable to time dependent, semilinear, scalar PDEs where the leading-order spatial derivative has a constant coefficient, is its ability to increase the accuracy of formally low-order finite difference schemes without major modification to the basic numerical algorithm. Through straightforward numerical analysis arguments, we explain the origin of the boost in accuracy and estimate the computational cost of the resulting numerical method. We demonstrate the utility of optimal time step (OTS) selection combined with non-iterative defect correction (NIDC) on several different types of finite difference schemes for a wide array of classical linear and semilinear PDEs in one and more space dimensions on both regular and irregular domains.     

Numerical performance of parallel group explicit solvers for the solution of fourth order elliptic equations

Many applications in applied mathematics and engineering involve numerical solutions of partial differential equations (PDEs). Various discretisation procedures such as the finite difference method result in a problem of solving large, sparse systems of linear equations. In this paper, a group iterative numerical scheme based on the rotated (skewed) five-point finite difference discretisation is proposed for the solution of a fourth order elliptic PDE which represents physical situations in fluid mechanics and elasticity. The rotated approximation formulas lead to schemes with lower computational complexities compared to the centred approximation formulas since the iterative procedure need only involve nodes on half of the total grid points in the solution domain. We describe the development of the parallel group iterative scheme on a cluster of distributed memory parallel computer using Message-Passing Interface (MPI) programming environment. A comparative study with another group iterative scheme derived from the centred difference formula is also presented. A detailed performance analysis of the parallel implementations of both group methods will be reported and discussed.     

Numerical treatment for nonlinear Brusselator chemical model

Nowadays, numerical models have great importance in every field of science, especially for solving the nonlinear differential equations, partial differential equations, biochemical reactions, etc. The total time evolution of the reactant species which interacts with other species is simulated by the Runge-Kutta of order four (RK4) and by Non-Standard finite difference (NSFD) method. A NSFD model has been constructed for the biochemical reaction problem and numerical experiments are performed for different values of discretization parameter h. The results are compared with the well-known numerical scheme, i.e. RK4. The developed scheme NSFD gives better results than RK4.     

Semi‐implicit schemes for transient Navier–Stokes equations and eddy viscosity models

This study presents two computational schemes for the numerical approximation of solutions to eddy viscosity models as well as transient Navier–Stokes equations. The eddy viscosity model is one example of a class of Large Eddy Simulation models, which are used to simulate turbulent flow. The first approximation scheme is a first order single step method that treats the nonlinear term using a semi‐implicit discretization. The second scheme employs a two step approach that applies a Crank–Nicolson method for the nonlinear term while also retaining the semi‐implicit treatment used in the first scheme. A finite element approximation is used in the spatial discretization of the partial differential equations. The convergence analysis for both schemes is discussed in detail, and numerical results are given for two test problems one of which is the two dimensional flow around a cylinder. © 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2009     

On the practical use of the spectral homotopy analysis method and local linearisation method for unsteady boundary-layer flows caused by an impulsively stretching plate

This paper expands the ideas of the spectral homotopy analysis method to apply them, for the first time, on non-linear partial differential equations. The spectral homotopy analysis method (SHAM) is a numerical version of the homotopy analysis method (HAM) which has only been previously used to solve non-linear ordinary differential equations. In this work, the modified version of the SHAM is used to solve a partial differential equation (PDE) that models the problem of unsteady boundary layer flow caused by an impulsively stretching plate. The robustness of the SHAM approach is demonstrated by its flexibility to allow linear operators that are partial derivatives with variable coefficients. This is seen to significantly improve the convergence and accuracy of the method. To validate accuracy of the the present SHAM results, the governing PDEs are also solved using a novel local linearisation technique coupled with an implicit finite difference approach. The two approaches are compared in terms of accuracy, speed of convergence and computational efficiency.     

Compact difference methods applied to initial-boundary value problems for mixed systems

Summary. An initial--boundary value problem to a system of nonlinear partial differential equations, which consists of a hyperbolic and a parabolic part, is taken into consideration. The problem is discretised by a compact finite difference method. An approximation of the numerical solution is constructed, at which the difference scheme is linearised. Nonlinear convergence is proved using the stability of the linearised scheme. Finally, a computational experiment for a noncompact scheme is presented. Received May 20, 1995     

ALTERNATING DIRECTION FINITE ELEMENT METHOD FOR SOME REACTION DIFFUSION MODELS

This paper is concerned with some nonlinear reaction - diffusion models. To solve this kind of models, the modified Laplace finite element scheme and the alternating direction finite element scheme are established for the system of patrical differential equations. Besides, the finite difference method is utilized for the ordinary differential equation in the models. Moreover, by the theory and technique of prior estimates for the differential equations, the convergence analyses and the optimal L^2- norm error estimates are demonstrated.     

Asymptotics of generalized derangements

An adaptive wavelet-based method is proposed for solving TV(total variation)–Allen–Cahn type models for multi-phase image segmentation. The adaptive algorithm integrates (i) grid adaptation based on a threshold of the sparse wavelet representation of the locally-structured solution; and (ii) effective finite difference on irregular stencils. The compactly supported interpolating-type wavelets enjoy very fast wavelet transforms, and act as a piecewise constant function filter. These lead to fairly sparse computational grids, and relax the stiffness of the nonlinear PDEs. Equipped with this algorithm, the proposed sharp interface model becomes very effective for multi-phase image segmentation. This method is also applied to image restoration and similar advantages are observed.     

Reduction of computational errors using nonstandard finite difference models

A previously reported bifurcation technique is applied to the construction of nonstandard finite difference representations of systems of nonlinear differential equations. This technique provides a measure of the deviation between bifurcation parameters obtained from fixed step representations of the nonlinear system and the values of the parameters determined from computational experiments. Since this deviation or ‘error’ is characteristic of a particular scheme, we have used this measure to construct low-error nonstandard representations. We present results from several nonlinear test models which show that such nonstandard schemes yield orbits that followed closely the expected dynamics and also provide a large reduction in the computational error in comparison to standard numerical integration schemes. Finally, we outline a criteria for controlling possible numerical overflow in fixed step-size schemes.     

An artificial boundary method for the Hull-White model of American interest rate derivatives

The Hull-White (HW) model is a widely used one-factor interest rate model because of its analytical tractability on liquidly traded derivatives, super-calibration ability to the initial term structure and elegant tree-building procedure. As an explicit finite difference scheme, lattice method is subject to some stability criteria, which may deteriorate the computational efficiency for early exercisable derivatives. This paper proposes an artificial boundary method based on the partial differential equations (PDEs) to price interest rate derivatives with early exercise (American) feature under the HW model. We construct conversion factors to extract the market information from the zero-coupon curve and then reduce the infinite computational domain into a finite one by using an artificial boundary on which an exact boundary condition is derived. We then develop an implicit θ-scheme with unconditional stability to solve the PDE in the reduced bounded domain. With a finite computational domain, the optimal exercise strategy can be determined efficiently. Our numerical examples show that the proposed scheme is accurate, robust to the truncation size, and more efficient than the popular lattice method for accurate derivative prices. In addition, the singularity-separating technique is incorporated into the artificial boundary method to enhance accuracy and flexibility of the numerical scheme.