查询词典 regularization

The inconsistencies of dimensional reduction and naive dimensional regularization in dealing withChern-Simons-matter theory are analyzed.The consistent dimensional regularization combiningwith higher covariant derivative regularization is adopted to consider Chern-Simons field theorycoupled to complex scalar and spinor field.All the local parts of one-loop two-point functionsand three-point functions are computed.Slavnov-Taylor identity is combined with these explicitcalculation results to give the one-loop local effective action.The finite gauge invariant quantumcorrection is shown and finite wave function renormalization constant for each field is defined.Thelocal part of one-loop three gauge field vertex is especially evaluated and it is verified that thereexists a renormalization choice compatible with BRST symmetry.

然后计算了所有的两点函数和三点函数单圈修正的定域部分，利用S-T恒等式给出了单圈定域有效作用量，定义了场的重正化常数，发现物质场和规范场都存在有限的规范不变的量子修正，并讨论了这些有限的规范不变的量子修正的物理意义，进而通过考察单圈三规范场顶角，表明存在与BRST对称性相容的重正化选择。5、在背景场方法的框架下，选择高阶协变导数正规化与维数正规化的杂化正规化方案计算了背景场两点函数的两圈量子修正，结果表明，标志紫外发散的极点项恰好抵消；进一步利用背景场方法中明显的规范对称性，证明背景场三点函数的两圈图贡献也是有限的。

It is a kind of itertive regularization method,and has the function adjusting regularization parameters automatically,so it overcomes the difficulties when solving the regularization parameters.

因此，对于这样的反问题，最后都可归结为极小化某些刻画问题的地质特征的测量值与理论计算值的误差平方和的函数的优化问题，约束条件为x≥0。

But these traditional methods have certain drawbacks and limitations. To contain solution's reliability and stability the regularization is often adopted. The effectiveness of a regularization method depends strongly on the choice of a good regularization parameter.

在反问题的理论及数值计算方面，国内外的科学家做了大量的工作，提出了不少经典的数学和物理方法，但这些传统的方法都有其一定的缺陷或局限性。

On the basis of that, the article gives a regularization filter and builds up a quite new method of regularization. It also discusses the calculation of regularization resolutions enor and the choice of regularization parameter, and proves that this method is the best to make the resolution have order optimality.

文中以此为依据给出了一个正则化滤子函数，从而建立一种新的正则化方法，并讨论了正则解的误差估计及正则参数的选取问题，证明了这种方法使正则解的误差具有渐进最优阶。

For the data set with noises, a regularization intropolation method is proposed according to regularization theory. The relation between the regularization intropolation method and radial basis function method is analysed and structure of regularization neural networks is proposed. RBF neural network is introduced by mortifying the regularization neural networks. Finally the approximation capacity of RBF neural networks is analysed. 4. A method of selecting the centers of hidden layer neurons of RBF neural networks is proposed.

首先从精确内插问题开始对RBF神经网络进行讨论，然后根据正则化理论提出了在数据集带有噪声的情况下的内插方法，并分析了这种内插方法和径向基函数方法之间的密切联系以及其对应的正则化神经网络结构，其次对正则化神经网络进行了修改，得到正则化神经网络的简化形式—RBF神经网络，最后分析了RBF神经网络的逼近性能。

Regularization is often used to overcome the ill-posedness, and Tikhonov regularization is the most common regularization method, but this kind of regularization will cause the sharp edge of the reconstruction result to be blurred.

从数学上来说，超分辨率图像重建问题是一个病态问题，为了克服其病态性，需要对其进行规整化，其中最常用的Tikhonov规整化方法，但这种规整化会导致重建高分辨率图像边界被模糊。

The experiment results prove that the way with regularization technology is better than the way without regularization technology. In order to overcome the limitation of the regularization method, chapter 6 builds an irregular MRF model suitable for the motion estimation of feature point based on MAP-MRF frame. The energy function, which can reflect the joint probability distribution of motion parameters and the constraints relation of local 3D motion parameters, is established in irregular MRF.

为了解决正则化方法只能分析非刚体局部三维运动的缺点，第6章在基于MAP-MRF的分析框架中建立了与特征点运动估计相对应的非规则MRF模型，构造了非规则MRF模型中反映非刚体局部三维运动参数之间约束关系和运动参数联合概率分布的能量函数，通过能量函数最小化估计运动参数。

The reconstruction problem is ill-posed, so two optimal criterions, the least module and the smoothness criterion base on Tikhonov regularization technique, are introduced into reconstruction algorithm. Many regularization parameters choice strategies are investigated, and the TPA(Two—Parameter Algorithm) strategy which is based on the Morozov discrepancy principles, is implemented in two regularization reconstruction algorithms.Numerical experiment results show that the nonnegative and smoothness constraint condition can overcome the difficulty of iteration semiconvergent, preconditioned technique can improve convergence rate and reconstruction accuracy, smoothness regularization criterion can meliorate ill-posed problem of reconstruction and enhance iteration stability, and the TPA is an effective strategy of regularization parameters choice.

数值试验表明：在共轭梯度法中引入非负约束和光滑约束改善了迭代的"半收敛"性，非负约束保证了解的非负性，光滑约束抑制了重建解的振荡现象，约束算法的重建精度与无约束算法相比大幅度提高；在约束共轭梯度重建算法中引入预优技术，可以加快算法的收敛速度，提高迭代的稳定性和重建精度；引入光滑准则的正则化技术可以有效改善图像重建问题的不适定性，加快迭代的收敛速度，提高迭代的稳定性和图像重建质量，计算正则参数的TPA算法在闪光照相图像重建中是有效的。

This thesis is divided into six parts. The first chapter is preface, the current status of research in the inverse problems for parabolic partial differential equations is reported; the second chapter is "regularization methods for numerical differentiation and their applications ", in this chapter we investigate many regularization methods from a viewpoint of regularization theory and algorithm, some applications in the inverse problems for parabolic partial differential equations are given; the third chapter is "spectral regularization methods". Based on Fourier analysis, within the framework of regularization theory, we apply the spectral methods to some ill-posed problems. Many numerical experiments are done in order to show the validity of the methods; the fourth chapter is devoted to wavelet dual least squares method and a revised wavelet method; in the fifth chapter,we combine finite difference method with method of lines and apply it to the backward heat conduction problem in time; in the sixth chapter "identification problems for unknown source ", the essence and the degree of two problems related to source identification are pointed out, at the same time, some numerical methods are reported.

本文分为六个部分，第一章前言简要分析了国内外抛物型偏微分方程反问题的研究现状；第二章数值微分的正则化及其应用从正则化理论和算法的角度出发，考察了许多正则化方法，还给出了数值微分在抛物型偏微分方程反问题的一些应用；第三章谱正则化方法是在Fourier分析的基础上，在一般正则化理论的框架下，给出了这种方法在各种不适定问题中的应用，数值实验表明谱方法是有效的；第四章研究了小波对偶最小二乘方法和改进的小波方法；第五章主要研究了有限差分方法结合线方法在时间反向热传导问题中的应用；第六章是未知源识别问题，主要指出了两类未知源问题的不适定程度和不适定本质，同时报告了一些数值方法。

The reconstruction problem is ill-posed, so two optimal criterions, the least module and the smoothness criterion base on Tikhonov regularization technique, are introduced into reconstruction algorithm. Many regularization parameters choice strategies are investigated, and the TPA(Two—Parameter Algorithm) strategy which is based on the Morozov discrepancy principles, is implemented in two regularization reconstruction algorithms.Numerical experiment results show that the nonnegative and smoothness constraint condition can overcome the difficulty of iteration semiconvergent, preconditioned technique can improve convergence rate and reconstruction accuracy, smoothness regularization criterion can meliorate ill-posed problem of reconstruction and enhance iteration stability, and the TPA is an effective strategy of regularization parameters choice.

数值试验表明：在共轭梯度法中引入非负约束和光滑约束改善了迭代的&半收敛&性，非负约束保证了解的非负性，光滑约束抑制了重建解的振荡现象，约束算法的重建精度与无约束算法相比大幅度提高；在约束共轭梯度重建算法中引入预优技术，可以加快算法的收敛速度，提高迭代的稳定性和重建精度；引入光滑准则的正则化技术可以有效改善图像重建问题的不适定性，加快迭代的收敛速度，提高迭代的稳定性和图像重建质量，计算正则参数的TPA算法在闪光照相图像重建中是有效的。

But in the course of internationalization, they meet with misunderstanding and puzzlement.

许多企业已经意识到了这一点，但在国际化的进程中，仍存在一些误区与困惑。

Inorder toaccomplish this goal as quickly as possible, we'll beteamingup with anexperienced group of modelers, skinners, and animatorswhosenames willbe announced in the coming weeks.

为了尽快实现这个目标，我们在未来数周内将公布与一些有经验的模型、皮肤、动画制作小组合作。