1 Everybody's first book on Regularization Theory.

2 By apriori choice of the regularization parameter respectively, the optimum asymptotic convergence order of the regularized solution is obtained.

3 In this paper, Bayesian Regularization algorithm and BP neural network were combined to forecast submarine sonar self-noise.

4 In this paper, a modified Tikhonov regularization CT image reconstruction algorithm from limited - angle was proposed.

5 The experimental results show that the regularization algorithm of the restoration of bar code signal can restrain the noise effectively when it is eliminating the effect of the point spread function.

6 Regularization is an effective way to eliminate such an instability.

7 Editing modernization is based on the regularization of editing work.

8 Total variation regularization method is a good choice to this problem.

9 By using the Tikhonov Regularization numerical inversion of black body radiation are discussed.

10 The mathematical solution for ill-posed problems is regularization. The computational foundation for deformable models is just regularization.

11 By using the Tikhonov Regularization Method, the related techniques for the numerical inversion of black body radiation are discussed.

12 By applying Argumented Lagrangian regularization techniques, the total variation restoration model was transformed into a system of nonsmooth equations.

13 The method of regularization and the technique of upper and lower solutions are employed to show the local existence and the continuation of the positive classical solution of the above problem.

14 Also an explicit solution of regularization to a special problem is constructed.

15 Based on the analysis of basic principle of electrical capacitance tomography and the image reconstruction algorithm, a conjugate gradient algorithm with optimized regularization is proposed.

16 A new framework of mollification methods based on L - generalized solution regularization Methods : Was proposed.

17 A new framework of mollification methods based on L-generalized solution regularization methods was proposed.

18 Therefore, maximum a posteriori estimates can be regarded as regularization ( regularization ) of the maximum likelihood estimate.

19 The techniques include extracting image edges, fitting a curve and pattern regularization.

20 This thesis analyzes the theoretics of a space - adaptive regularization method for blind image restoration.

21 The existence and stability of the optimal control is established based on the parabolic regularization method and the weak convergence technique.

22 Subsequently, as a important property, the time invariance of support set of solutions of regularization is proved. Also an explicit solution of regularization to a special problem is constructed.

23 Shui characters are classified into ancient and current characters based on the regularization of Shui Characters.

24 This paper proposes a blind image restoration algorithm iteratively using wavelet denoising and total variation regularization.

25 It is difficult for us to get the thermal contact resistance directly. In this paper, an inversion model and solve it by regularization method has been developed.

26 To solve the ill-posed problem in electrical capacitance tomography(ECT), a new image reconstruction algorithm based on total variation(TV) regularization is proposed.

27 Though restricted to early vision, it contains an easy - to - read introduction to ill-posed problems and regularization methods.

28 The ill-posedness inherent in the bandlimited signal extrapolation problem can be treated by means of regularization parameters.

29 So various methods are proposed by scholars to solve these problems, such as pulse spectrum method, the best perturbation method, Monte Carlo method, optimized and regularization method.

30 Theoretically , canonical truncated singular value decomposition ( TSVD ) is considered a good regularization method in solving ill - posed problems.

31 In this paper, we discuss the numerical differentiation problem by Tikhonov regularization.

32 The problems of regularization, freeness of impulse, stability and pole-placement of general descriptor systems(GDS) are studied by using dynamic compensation.

33 We proposed to use wavelets and a regularization method to solve the small sample problem.

34 Proposed a linear programming algorithm to replace quadratic programming in support vector machine solution process and sparse regularization, and guaranteed the sparseness of the solution.

35 In order to filter the noisiness in the observed data, a new data processing method, so called the optimal regularization smoothing procedure, is provided in this paper.

36 RKHS will be an essential tool a connection between Regularization Theory and Statistical Learning Theory.

37 A brief, somewhat unorthodox, review of Regularization Theory is presented.

38 A wavelet based adaptive regularization scheme for blind image restoration is presented.

39 Restoration of barcode signal is an ill-posed problem in mathematical physical inverse problem; the most successful approach to which is regularization method.

40 A constrained optimization problem in primal weight space with incorporation of a regularization term was discussed. The dual problem was solved by using the kernel trick.

41 Rule simplification and regularization:Rule simplification and regularization are a type of spontaneous morphological rule change that involves exceptional plural forms of nouns.

42 In order to solve the ill - posedof heat conduction equation, discrete regularization method is used.

43 The usual methods include regularization method, iterative method, stochastic method and so on.

44 The article discusses over regularization Methods: The first kind of integral equation.

45 Economic globalization and regional regularization are the epochal characteristics in the world of today.

46 The generalized cross - validation leads to a good selection of regularization parameters also.

47 Based on TIKHONOV regularization theorem, a new regularizer, which has explicitly physical meaning, is chosen to mitigate the ill-condition of the normal matrix.

48 The relation between network architecture and the proposed regularization approach is unveiled.

49 A stable solution of an ill-posed inverse problem can be obtained by utilizing the regularization methods in the objective function.

50 In traditional approach, people use l_2 -norm to measure data approximation item and regularization item in regularized image restoration and super-restoration in spatial domain.