求解病态问题的一种改进的Tikhonov正则化--(1)正则化方法的建立

对于带有右端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     

应用正则化子建立求解不适定问题的正则化方法的探讨

根据紧算子的奇异系统理论,提出一种新的正则化子进而建立了一类新的求解不适定问题的正则化方法。分别通过正则参数的先验选取和后验确定方法,证明了正则解的收敛性并得到了其最优的渐近收敛阶;验证了应用Newton迭代法计算最佳参数的可行性。最后建立了当算子与右端均有扰动时相应的正则化求解策略。文中所述方法完善了一般优化正则化策略的构造理论。     

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．     

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。     

基于奇异值分解建立的一种新的正则化方法

根据紧算子的奇异系统理论，引入一种正则化滤子函数，从而建立一种新的正则化方法来求解右端近似给定的第一类算子方程，并给出了正则解的误差分析。通过正则参数的先验选取，证明了正则解的误差具有渐进最优阶。      

一种新的正则化方法的正则参数的最优后验选取

应用紧算子的奇异系统和广义Arcangeli方法后验选取正则参数，证明了文[1]中所建立的求解第一类算子方程的正则化方法是收敛的，且正则解具有最优的渐近阶。     

解第一类算子方程的一种迭代正则化方法

提出了一种求解第一类算子方程的新的迭代正则化方法,并依据广义Arcangeli方法选取正则参数,建立了正则解的收敛性.与通常的Tikhonov正则化方法相比较,提高了正则解的渐近阶估计.     

求解第一类Fredholm积分方程的一种新的正则化算法

应用一种新的正则化方法建立了一类新的求解第一类Fredholm积分方程的正则化算法, 并借助Matlab软件给出了数值算例.数值结果与理论分析基本一致,而且表明文中建立的正则化比通常的Tikhonov正则化更精确.     

一种新的正则化方法求解热传导方程的侧边值问题

考虑了四分之一平面内的热传导方程的侧边值问题,这类问题是严重不适定的.采用传统拟逆方法得到该问题的一个近似解,但发现它并不是一个正则化解.有趣的是,对解的分母项加以修正便可以得到侧边值问题的一个正则化解,进而提出了一种新的正则化方法,并分别给出先验和后验两种正则化参数选取规则下的Hlder型误差估计.数值实验验证了所提方法的可行性和有效性.     

补偿紧性在奇异四阶和六阶摄动偏微分方程中的应用

在这篇文章中，我们应用补偿紧性方法，能量方法得到了一类四阶、六阶奇异摄动微分方程解的收敛性问题，并进一步提高了解的正则性．     

REGULARIZATION METHOD FOR IMPROVING OPTIMAL CONVERGENCE RATE OF THE REGULARIZED SOLUTION OF ILL-POSED PROBLEMS

1IntroductionThestudyoflllallymathematicalphysicsproblemsleadstosolvingoperatorequatiollsofthefirstkind,andtheoperatorequatiollsofthefirstkindaretypicallyill--posedprobellis[1,2,3,4].Themethodsforsolvillgill-posedproblellishavebeenstudiedbyagreatnumberofresearchers.WementionTikhonovandArsellill[2],Morozov[3]IGroetscll[4],Engll51,HouandLi['],ChenandHouI7]alldoillerscholars.Illtheirresearches,they11avediscussedtheproblemoffindingstableapproxilllatesolutiollsand11aveillvestigatedtileconverge…     

A Modified Tikhonov Regularization for Linear Operator Equations

We construct with the aid of regularizing filters a new class of improved regularization methods, called modified Tikhonov regularization (MTR), for solving ill-posed linear operator equations. Regularizing properties and asymptotic order of the regularized solutions are analyzed in the presence of noisy data and perturbation error in the operator. With some accurate estimates in the solution errors, optimal convergence order of the regularized solutions is obtained by a priori choice of the regularization parameter. Furthermore, numerical results are given for several ill-posed integral equations, which not only roughly coincide with the theoretical results but also show that MTR can be more accurate than ordinary Tikhonov regularization (OTR).     

Convergent Algorithm Based on Progressive Regularization for Solving Pseudomonotone Variational Inequalities

In this paper, we extend the Moreau-Yosida regularization of monotone variational inequalities to the case of weakly monotone and pseudomonotone operators. With these properties, the regularized operator satisfies the pseudo-Dunn property with respect to any solution of the variational inequality problem. As a consequence, the regularized version of the auxiliary problem algorithm converges. In this case, when the operator involved in the variational inequality problem is Lipschitz continuous (a property stronger than weak monotonicity) and pseudomonotone, we prove the convergence of the progressive regularization introduced in Refs. 1, 2.     

A METHOD TO APPROACH OPTIMAL RESTORATION IN IMAGE RESTORATION PROBLEMS WITHOUT NOISE ENERGY INFORMATION

This paper proposes a new image restoration technique, in which the resulting regularized image approximates the optimal solution steadily. The affect of the regular-ization operator and parameter on the lower band and upper band energy of the residue of the regularized image is theoretically analyzed by employing wavelet transform. This paper shows that regularization operator should generally be lowstop and highpass. So this paper chooses a lowstop and highpass operator as regularization operator, and construct an optimization model which minimizes the mean squares residue of regularized solution to determine regularization parameter. Although the model is random, on the condition of this paper, it can be solved and yields regularization parameter and regularized solu-tion. Otherwise, the technique has a mechanism to predict noise energy. So, without noisei nformation, it can also work and yield good restoration results.     

A Generalization of the Regularization Method to the Singularly Perturbed Integro-Differential Equations With Partial Derivatives

We generalize the Lomov’s regularization method to partial integro-differential equations. It turns out that the procedure for regularization and the construction of a regularized asymptotic solution essentially depend on the type of the integral operator. The most difficult is the case, when the upper limit of the integral is not a variable of differentiation. In this paper, we consider its scalar option. For the integral operator with the upper limit coinciding with the variable of differentiation, we investigate the vector case. In both cases, we develop an algorithm for constructing a regularized asymptotic solution and carry out its full substantiation. Based on the analysis of the principal term of the asymptotic solution, we study the limit in solution of the original problem (with the small parameter tending to zero) and solve the so-called initialization problem about allocation of a class of input data, in which the passage to the limit takes place on the whole considered period of time, including the area of boundary layer.     

A regularized parameter choice in regularization for a common solution of a finite system of ill-posed equations involving Lipschitz continuous and accretive mappings

In this paper, we present a regularized parameter choice in a new regularization method of Browder-Tikhonov type, for finding a common solution of a finite system of ill-posed operator equations involving Lipschitz continuous and accretive mappings in a real reflexive and strictly convex Banach space with a uniformly Gateaux differentiate norm. An estimate for convergence rates of regularized solution is also established.     

动力系统方法解决无界线性算子方程

针对反问题中出现的第一类算子方程Au=f,其中A是实Hilbert空间H上的一个无界线性算子利用动力系统方法和正则化方法,求解上述问题的正则化问题的解:u'(t)=-A~*(Au(t)-f)利用线性算子半群理论可以得到上述正则化问题的解的半群表示,并证明了当t→∞时,所得的正则化解收敛于原问题的解.