Convergence analysis of an optimally accurate frozen multi-level projected steepest descent iteration for solving inverse problems

In this paper, we introduce a novel projected steepest descent iterative method with frozen derivative. The classical projected steepest descent iterative method involves the computation of derivative of the nonlinear operator at each iterate. The method of this paper requires the computation of derivative of the nonlinear operator only at an initial point. We exhibit the convergence analysis of our method by assuming the conditional stability of the inverse problem on a convex and compact set. Further, by assuming the conditional stability on a nested family of convex and compact subsets, we develop a multi-level method. In order to enhance the accuracy of approximation between neighboring levels, we couple it with the growth of stability constants. This along with a suitable discrepancy criterion ensures that the algorithm proceeds from level to level and terminates within finite steps. Finally, we discuss an inverse problem on which our methods are applicable.     

Determination of an unknown coefficient in a nonlinear heat equation

The problem of determining an unknown term k(u) in the equation k(u)u_t=(k(u)u_x)_x is considered in this paper. Applying Tikhonov's regularization approach, we develop a procedure to find an approximate stable solution to the unknown coefficient from the overspecified data.     

The Levenberg-Marquardt method applied to a parameter estimation problem arising from electrical resistivity tomography

An efficient and robust electrical resistivity tomographic inversion algorithm based on the Levenberg-Marquardt method is considered to obtain quantities like grain size, spatial scale and particle size distribution of mineralized rocks. The corresponding model in two dimensions is based on the Maxwell equations and leads to a partial differential equation with mixed Dirichlet-Neumann boundary conditions. The forward problem is solved numerically with the finite-difference method. However, the inverse problem at hand is a classical nonlinear and ill-posed parameter estimation problem. Linearizing and applying the Tikhonov regularization method yields an iterative scheme, the Levenberg-Marquardt method. Several large systems of equations have to be solved efficiently in each iteration step which is accomplished by the conjugate gradient method without setting up the corresponding matrix. Instead fast matrix-vector multiplications are performed directly. Therefore, the derivative and its adjoint for the parameter-to-solution map are needed. Numerical results demonstrate the performance of our method as well as the possibility to reconstruct some of the desired parameters.     

On the uniqueness and reconstruction for an inverse problem of the fractional diffusion process

Consider an inverse problem for the time-fractional diffusion equation in one dimensional spatial space. The aim is to determine the initial status and heat flux on the boundary simultaneously from heat measurement data given on the other boundary. Using the Laplace transform and the unique extension technique, the uniqueness for this inverse problem is proven. Then we construct a regularizing scheme for the reconstruction of boundary flux for known initial status. The convergence rate of the regularizing solution is established under some a priori information about the exact solution. Moreover, the initial distribution can also be recovered approximately from our regularizing scheme. Finally we present some numerical examples, which show the validity of the proposed reconstruction scheme.     

An iterative stabilization method for the evaluation of unbounded operators

We investigate a stable iterative approximate evaluation method for closed unbounded operators such as those that occur frequently in inverse problems. Convergence theorems, as well as order of approximation results, are proved for both a priori and a posteriori schemes for choosing the stopping index of the iteration.

     

On a radially symmetric inverse heat conduction problem

In this paper, we treat an inverse problem for a radially symmetric heat equation, which arises from non-destructive evaluation by thermal imaging. The problem can also be considered as an inverse heat conduction problem. Based on a weighted energy method, we give a conditional stability estimate. A feasible regularization method is provided for numerical simulation. The reconstruction experiment is done for verifying the efficiency of the regularization method.     

Identification of a spacewise dependent heat source

The inverse problem of determining the temperature of a heat conductor together with an unknown spacewise dependent heat source from measured final data or time-average temperature observation is studied. The weak solution theory is applied for calculating the gradient of the least-squares functional that is minimized. For the general case when the heat source is the product between a known function h(x,t)$h(x\text{,}t)$ and the unknown source function f(x)$f(x)$ new explicit formulae, derived via the solution of the corresponding adjoint problem, are obtained. Numerical results obtained using the conjugate gradient method are presented and discussed.     

On the Well-Posedness of Determination of Two Coefficients in a Fractional Integrodifferential Equation

The authors study an inverse problem for a fractional integrodifferential equation, which aims to determine simultaneously two time varying coefficients, a kernel function and a source function, from the additional integral overdetermination condition. By using the fixed point theorem in suitable Sobolev space, the global existence and uniqueness results of this inverse problem are obtained.     

关于分形插值函数的连续性和可微性

获得了由迭代函数系统(IFS)定义的两类分形插值函数具有Hlder连续性的充分条件,给出了这两类分形插值函数连续可微的充要条件,并证明了可微分形插值函数的导函数是由关联IFS生成的分形插值函数.     

A fractional Tikhonov method for solving a Cauchy problem of Helmholtz equation

In this paper, we study a fractional Tikhonov regularization method (FTRM) for solving a Cauchy problem of Helmholtz equation in the frequency domain. On the one hand, the FTRM retains the advantage of classical Tikhonov method. On the other hand, our method can prevent the effect of oversmoothing of classical Tikhonov method and conveniently control the amount of damping. The convergence error estimates between the exact solution and its regularization approximation are constructed. Several interesting numerical examples are provided, which validate the effectiveness of the proposed method.     

A variational conjugate gradient method for determining the fluid velocity of a slow viscous flow

The problem considered is that of determining the fluid velocity for linear hydrostatics Stokes flow of slow viscous fluids from measured velocity and fluid stress force on a part of the boundary of a bounded domain. A variational conjugate gradient iterative procedure is proposed based on solving a series of mixed well-posed boundary value problems for the Stokes operator and its adjoint. In order to stabilize the Cauchy problem, the iterations are ceased according to an optimal order discrepancy principle stopping criterion. Numerical results obtained using the boundary element method confirm that the procedure produces a convergent and stable numerical solution.     

固定-固定型无阻尼弹簧质点系统的质量约束问题

本文讨论了系统总质量约束下的固定一固定型无阻尼弹簧质点系统的构造问题，得到了该问题的可解性条件，给出了解的表达式和数值算法，算例说明算法是有效的．     

On Consistency of the Nearest Neighbor Estimator of the Density Function and Its Applications

In this paper, we mainly study the consistency of the nearest neighbor estimator of the density function based on asymptotically almost negatively associated samples. The weak consistency,strong consistency, uniformly strong consistency and the convergence rates are established under some mild conditions. As applications, we further investigate the strong consistency and the rate of strong consistency for hazard rate function estimator.     

On solvability and regularity of a parametrized version of optimality conditions

We investigate a linear homotopyF(·,t) connecting an appropriate smooth equationG=0 with Kojima's (nonsmooth) systemK=0 describing critical points (primal —dual) of a nonlinear optimization problem (NLP) in finite dimension.Fort=0, our system may be seen e.g. as a starting system for an embedding procedure to determine a critical point to NLP. Fort1, it may be regarded as a regularization ofK.Conditions for regularity (necessary and sufficient) and solvability (sufficient) are studied. Though, formally, they can be given in a unified way, we show that their meaning differs fort < 1 andt=1. Particularily, no MFCQ-like condition must be imposed in order to ensure regularity fort < 1.     

一类由一维概率密度函数构造多维概率密度函数的方法

将文献[1]给出的由一维连续型随机变量的概率密度函数构造二维连续型随机变量的概率密度函数的方法,推广为由一维连续型随机变量的概率密度函数构造三维连续型随机变量的概率密度函数的情况,并作出了证明和举例说明.说明利用本文的方法构造多维概率密度函数,其方法简单易行.     

二元函数四条性质之间的关系

二元函数的连续性,偏导数存在性,偏导数连续性以及可微性是二元函数的四条经典性质,它们之间的关系一直是学生的疑惑点,本文结合严格的证明和典型的反例给出四条性质之间关系的详尽阐释.     

一维粘弹性波动方程弹性系数的识别方法

本文就一维粘弹性波动方程弹性系数的求解问题，给出了一个新的求解方法．通过对算法进行分析可知，该方法具有较小的计算量，并且具较好的数值稳定性．数值模拟表明了该方法的可行性及有效性．     

On a quasi-reversibility regularization method for a Cauchy problem of the Helmholtz equation

In this paper, we consider the Cauchy problem for the Helmholtz equation in a rectangle, where the Cauchy data is given for y=0 and boundary data are for x=0 and x=π. The solution is sought in the interval 0<y≤1. A quasi-reversibility method is applied to formulate regularized solutions which are stably convergent to the exact one with explicit error estimates.