不适定问题的迭代Tikhonov正则化方法

Tikhonov正则化方法是研究不适定问题最重要的正则化方法之一,但由于这种方法的饱和效应,使得不可能随着解的光滑性假设的提高而提高收敛率,即不能使正则解与准确解的误差估计达到阶数最优．本文所讨论的迭代的Tikhonov正则化方法对此进行了改进,保证了误差估计总可以达到阶数最优．数值试验结果表明计算效果良好．     

Tikhonov 正则化的饱和性与逆结果及后验参数选取 *

对解非线性不适定问题的Tikhonov正则化证明了饱和性与一些逆结果 ,并考虑了正则化参数的最优后验选取 .     

非线性不适定问题的Tikhonov正则化的参数选取方法

在Ｔｉｋｈｏｎｏｖ正则化中，如何选取正则参数极为重要，直至现在，仍有许多问题期待解决．本文对非线性不适定问题考虑了Ｔｉｋｈｏｎｏｖ正则化，提出了一个新的简单的正则参数的最优选取法，并对由此得到的正则参数，研究了Ｔｉｋｈｏｎｏｖ正则化解的收敛性，并且当ｘ－最小范数解满足“源条件”时，在适当的条件下，导出了最优收敛率．     

一类非线性不适定问题的Tikhonov正则化

本文在B anach空间中,研究一类非线性不适定问题的正则化,所研究的算子是多值的,且是近拟的,假定原始问题是可解的,利用带双参数的T ikhonov正则化方法构造出逼近步骤.     

基于混沌粒子群算法的Tikhonov正则化参数选取

Tikhonov正则化方法是求解不适定问题最为有效的方法之一,而正则化参数的最优选取是其关键.本文将混沌粒子群优化算法与Tikhonov正则化方法相结合,基于Morozov偏差原理设计粒子群的适应度函数,利用混沌粒子群优化算法的优点,为正则化参数的选取提供了一条有效的途径.数值实验结果表明,本文方法能有效地处理不适定问题,是一种实用有效的方法.     

关于迭代Tikhonov正则化的最优正则参数选取

本文讨论了算子和右端都近似给定的第一类算子方程的迭代Ｔｉｋｈｏｎｏｖ正则化，给出了不依赖于准确解的任何信息但能得到最优收敛阶的正则参数选取法。     

约束Fractional Tikhonov正则化的模迭代方法

反问题是现在数学物理研究中的一个热点问题,而反问题求解面临的一个本质性困难是不适定性。求解不适定问题的普遍方法是:用与原不适定问题相“邻近”的适定问题的解去逼近原问题的解,这种方法称为正则化方法.如何建立有效的正则化方法是反问题领域中不适定问题研究的重要内容.当前,最为流行的正则化方法有基于变分原理的Tikhonov正则化及其改进方法,此类方法是求解不适定问题的较为有效的方法,在各类反问题的研究中被广泛采用,并得到深入研究.     

求解病态问题的一种改进的Tikhonov正则化：⑴正则化方法的建立

对于带有右扰动数据的第一类紧算子方程的病态问题。本文应用正则化子建立了一类新的正则化求解方法,称之为改进的Ｔｉｋｏｎｏｖ正则化;通过适当选取２正则参数,证明了正则解具有最优的渐近收敛阶,与通常的Ｔｉｋｈｏｎｏｖ正则化相比,这种改进的正则化可使正则解取到足够高的最优渐近阶。     

双调和方程柯西问题的修正的Tikhonov正则化方法

本文研究了双调和方程柯西问题,这类是不适定的,即问题的解(如果存在)不连续依赖于测量数据.首先在精确解的先验假设下给出问题的条件稳定性结果.接着利用修正的Tikhonov正则化方法求解此不适定问题.在先验和后验正则化参数选取规则下,给出正则解和精确解之间的误差估计式.最后给出几个数值例子验证此正则化方法求解此类反问题的有效性.     

用Tikhonov正则化方法求一阶和两阶的数值微分

Numerical differentiation is an ill-posed problem, which is important in scientific research and practical applications.In this paper, we use the Tikhonov regularization method to discuss the first and secord order derivatives of a smooth function. The error estimate is also given. And the numerical results prove that our method is applicable.     

MULTI-PARAMETER TIKHONOV REGULARIZATION FOR LINEAR ILL-POSED OPERATOR EQUATIONS

We consider solving linear ill-posed operator equations. Based on a multi-scale decomposition for the solution space, we propose a multi-parameter regularization for solving the equations. We establish weak and strong convergence theorems for the multi-parameter regularization solution. In particular, based on the eigenfunction decomposition, we develop a posteriori choice strategy for multi-parameters which gives a regularization solution with the optimal error bound. Several practical choices of multi-parameters are proposed. We also present numerical experiments to demonstrate the outperformance of the multiparameter regularization over the single parameter regularization.     

改进的Tikhonov 正则化及其正则解的最优渐近阶估计

对于算子与右端都有扰动的第一类算子方程建立了一类新的正则化方法(称为改进的 Ｔｉｋｈｏｎｏｖ正则化)．应用紧算子的奇异系统和广义 Ａｒｃａｎｇｅｌｉ方法后验选取正则参数,证明了正则解具有最优的渐近阶并给出了相应的算例分析．     

REGULARIZATION OF AN ILL-POSED HYPERBOLIC PROBLEM AND THE UNIQUENESS OF THE SOLUTION BY A WAVELET GALERKIN METHOD

We consider the problem K(x)u xx = u tt , 0 < x < 1, t ≥ 0, with the boundary condition u(0,t) = g(t) ∈ L 2 (R) and u x (0, t ) = 0, where K(x) is continuous and 0 < α≤ K (x) < +∞. This is an ill-posed problem in the sense that, if the solution exists, it does not depend continuously on g. Considering the existence of a solution u(x, ) ∈ H 2 (R) and using a wavelet Galerkin method with Meyer multiresolution analysis, we regularize the ill-posedness of the problem. Furthermore we prove the uniqueness of the solution for this problem.     

ON THE ASYMPTOTIC ORDER OF TIKHONOV REGULARIZATION WITH OPERATORS ANDDATA ERROR

1IntroductionAgreatmanylinearinverseproblemsofmathematicalphysicsmaybefi.allledinanabstractsettingaslinearoperatorequationsoftheform.Ti=y,(1)whichimplicitlydefinesthesolutionxoofthegivenproblem.ThedesiredsolutionxoisOftengi'venintermsoftheMoors-PenrosegeneralizedinverseT intheformxo=T y([1]).InallinterestingcasesthegeneralizedinverseisanunboundedoperatorandthechallengeisthentoprovideapproximationstotheunknownsolutionT ythatarestablewithrespecttoperturbationsinthedatay.'Aprototypefortheequat…     

AN IMPROVED ERROR ANALYSIS FOR FINITE ELEMENT APPROXIMATION OF BIOLUMINESCENCE TOMOGRAPHY

This paper is concerned with an ill-posed problem which results from the area of molecular imaging and is known as BLT problem. Using Tikhonov regularization technique, a quadratic optimization problem can be formulated. We provide an improved error estimate for the finite element approximation of the regularized optimization problem. Some numerical examples are presented to demonstrate our theoretical results.     

WEAK REGULARIZATION FOR A CLASS OF ILL-POSED CAUCHY PROBLEMS

This article is concerned with the ill-posed Cauchy problem associated with a densely defined linear operator A in a Banach space. A family of weak regularizing operators is introduced. If the spectrum of A is contained in a sector of right-half complex plane and its resolvent is polynomially bounded, the weak regularization for such ill-posed Cauchy problem can be shown by using the quasi-reversibility method and regularized semigroups. Finally, an example is given.