逼近转化论和泛系逼近论(Ⅳ)

Theorem 1 If 1≤p≤∞, f∈W_p~(l)(D), then ω_k(δ,f,W_p~(l)(D))≤c(‖f‖_(l)_p),if f∈C~〔k+l〕(D), then ω_k(δ, f,W_p~(l)(D))≤c(δ~kmax‖(D)~(k)f‖_(()p)), where c is independent of δ≥0 and f. Theorem 2 If f∈W_p~(r)H_M~(a)(〔a,b〕)is of period b-a<∞, then ‖f‖_((s)t)≤cM~d‖f‖_((u)υ)~e, where d=δ/θ, e=(θ-δ)/θ, p≥1, t≥υ≥1, r>s≥u, δ=s-u+     

一般线性方法的散逸稳定性

1 散逸动力系统 考虑初值问题 y′(t)=f(y),y(0)=y_0∈R~N,t≥0, (1.1)这里f:R~N→R~N是满足局部Lipschitz条件的连续映射,并满足条件 Re〈u,f(u)〉≤α-β‖u‖~2 u∈R~N,(1.2)其中α≥0,β>0,〈·,·〉是R~N中标准内积,‖·‖是相应的内积范数.设y(t)是问题(1.1)-(1.2)的一个真解,则 ‖y(t)‖~2≤α/β+e~(-2βt)(‖y_0‖~2-α/β) t≥0, (1.3)及 ‖y(t)‖≤max(‖y_0‖,α/β)　 t≥0,(1.4)     

COMPOSITION OPERATORS BETWEEN SOME WEIGHTED HARDY SPACES

Let D be the unit disc and H(D) be the set of all analytic functions on D. In [2], C. Cowen defined a space H = f ∈ H(D) : f(z) =sum from k=o to ∞ ak(z + 1)k, z∈ D, ‖f‖2 = sum from k=o to ∞ |ak|24k < ∞In this article, the authors consider the similar Hardy spaces with arbitrary weights and discuss some properties of them. Boundedness and compactness of composition operators between such spaces are also studied.     

Neumann边界条件下L~P-Poincaré不等式最优常数的估计

本文考虑在Neumann边界条件下,当π为有限测度时,对不等式π(|f—π(|f|~(p—2)f)|~p)Apπ(a|f′|~p),f∈D(Dp)中的最优常数Ap的估计.通过采用分割的方法可转化为Dirichlet边界条件的情况,进而得到了上下界的估计.并考虑当π为无穷测度时,在Neumann边界条件下不等式π(|f|~p)Apπ(a|f′|~p),f∈D(Dp)中常数Ap的上下界,给出了变分公式估计及显式估计.     

WEIGHTED A PRIORI ESTIMATES FOR SOLUTION OF (-△)~mu = f WITH HOMOGENEOUS DIRICHLET CONDITIONS

Let u be a weak solution of (-△)mu = f with Dirichlet boundary conditions in a smooth bounded domain Ω  Rn. Then, the main goal of this paper is to prove the following a priori estimate:‖u‖ Wω2 m,p(Ω) ≤ C ‖f‖ Lωp (Ω),where ω is a weight in the Muckenhoupt class Ap.     

关于分数阶积分与导数的性质

现将本文所用的预备知识叙述如下:1°假设f(x)在[a,b]上可积,当β>0,如果下列积分存在,则称fβ(x)为f(x)的β阶积分.如果f(x)是周期为2π的函数,同时f (x)在[0,2π]上的积分为零,这时f(x)的β阶积分由下列公式给出     

Weighted a priori estimates for solution of (−Δ)<Superscript><Emphasis Type="Italic">m</Emphasis></Superscript><Emphasis Type="Italic">u</Emphasis> = <Emphasis Type="Italic">f</Emphasis> with homogeneous dirichlet conditions

Let u be a weak solution of (-△)mu = f with Dirichlet boundary conditions in a smooth bounded domain Ω  Rn. Then, the main goal of this paper is to prove the following a priori estimate:‖u‖ Wω2 m,p(Ω) ≤ C ‖f‖ Lωp (Ω),where ω is a weight in the Muckenhoupt class Ap.     

COEFFICIENT MULTIPLIERS ON MIXED NORM SPACES

§1　IntroductionSuppose thatf is analytic in the open unit disc D in the complex plane.We defineMp(r,f) =12π∫2π0 | f(reiθ) | pdθ1 / p,0

相似文献   

A NOTE ON MORREY-NIKOL KII INEQUALITY

Let Q_0 be a Cube in R~n and u(x)∈L~p(Q_0).Suppose that∫_Q丨u(x t)-u(x)丨~pdx≤K~p丨t丨~(ap)丨Q丨~(1/β/n)for all parallel subcubes Q in Q_0 and for all t such that the integral makes sense with K≥0,0<α≤1, 0≤β≤n and p≥1.If αp=β,then u(x)is of bounded mean oscillation on Q_0(abbreviated to BMO(Q_0)),i.e.sup QQ_0 1/丨Q丨∫_Q丨u(x)-u_Q丨dx=‖u‖<∞,where u_Q is the mean value of u(x)over Q.     

单边条件下Fourier和的逼近

<正> §1.前言 设C_(2π)是周期2π的连续函数的全体.对于函数f∈C_(2π),记其范数为‖f‖,连续模为ω(f,δ).又将函数f(x)的Fourier级数之前n+1项和记作     

QTT-finite-element approximation for multiscale problems I: model problems in one dimension

Tensor-compressed numerical solution of elliptic multiscale-diffusion and high frequency scattering problems is considered. For either problem class, solutions exhibit multiple length scales governed by the corresponding scale parameter: the scale of oscillations of the diffusion coefficient or smallest wavelength, respectively. As is well-known, this imposes a scale-resolution requirement on the number of degrees of freedom required to accurately represent the solutions in standard finite-element (FE) discretizations. Low-order FE methods are by now generally perceived unsuitable for high-frequency coefficients in diffusion problems and high wavenumbers in scattering problems. Accordingly, special techniques have been proposed instead (such as numerical homogenization, heterogeneous multiscale method, oversampling, etc.) which require, in some form, a-priori information on the microstructure of the solution. We analyze the approximation properties of tensor-formatted, conforming first-order FE methods for scale resolution in multiscale problems without a-priori information. The FE methods are based on the dynamic extraction of principal components from stiffness matrices, load and solution vectors by the quantized tensor train (QTT) decomposition. For prototypical model problems, we prove that this approach, by means of the QTT reparametrization of the FE space, allows to identify effective degrees of freedom to replace the degrees of freedom of a uniform “virtual” (i.e. never directly accessed) mesh, whose number may be prohibitively large to realize computationally. Precisely, solutions of model elliptic homogenization and high-frequency acoustic scattering problems are proved to admit QTT-structured approximations whose number of effective degrees of freedom required to reach a prescribed approximation error scales polylogarithmically with respect to the reciprocal of the target Sobolev-norm accuracy ε with only a mild dependence on the scale parameter. No a-priori information on the nature of the problems and intrinsic length scales of the solution is required in the numerical realization of the presently proposed QTT-structured approach. Although only univariate model multiscale problems are analyzed in the present paper, QTT structured algorithms are applicable also in several variables. Detailed numerical experiments confirm the theoretical bounds. As a corollary of our analysis, we prove that for the mentioned model problems, the Kolmogorov n-widths of solution sets are exponentially small for analytic data, independently of the problems’ scale parameters. That implies, in particular, the exponential convergence of reduced basis techniques which is scale-robust, i.e., independent of the scale parameter in the problem.     

Analysis of linearized Galerkin-mixed FEMs for the time-dependent Ginzburg-Landau equations of superconductivity

A linearized backward Euler Galerkin-mixed finite element method is investigated for the time-dependent Ginzburg-Landau (TDGL) equations under the Lorentz gauge. By introducing the induced magnetic field σ = c u r l A as a new variable, the Galerkin-mixed FE scheme offers many advantages over conventional Lagrange type Galerkin FEMs. An optimal error estimate for the linearized Galerkin-mixed FE scheme is established unconditionally. Analysis is given under more general assumptions for the regularity of the solution of the TDGL equations, which includes the problem in two-dimensional nonconvex polygons and certain three dimensional polyhedrons, while the conventional Galerkin FEMs may not converge to a true solution in these cases. Numerical examples in both two and three dimensional spaces are presented to confirm our theoretical analysis. Numerical results show clearly the efficiency of the mixed method, particularly for problems on nonconvex domains.     

A reduced finite element formulation based on POD method for two-dimensional solute transport problems

A proper orthogonal decomposition (POD) method is applied to a usual finite element (FE) formulation for two-dimensional solute transport problems with real practical applied background such that it is reduced into a reduced FE formulation with lower dimensions and high enough accuracy. The error estimates between the reduced POD FE solutions and the usual FE solutions are provided. It is shown by numerical examples that the results of numerical computation are consistent with theoretical conclusions. Moreover, it is also shown that this validates the feasibility and efficiency of POD FE method.     

A reduced FE formulation based on POD method for hyperbolic equations

A proper orthogonal decomposition (POD) method was successfully used in the reduced-order modeling of complex systems. In this paper, we extend the applications of POD method, namely, apply POD method to a classical finite element (FE) formulation for second-order hyperbolic equations with real practical applied background, establish a reduced FE formulation with lower dimensions and high enough accuracy, and provide the error estimates between the reduced FE solutions and the classical FE solutions and the implementation of algorithm for solving reduced FE formulation so as to provide scientific theoretic basis for service applications. Some numerical examples illustrate the fact that the results of numerical computation are consistent with theoretical conclusions. Moreover, it is shown that the reduced FE formulation based on POD method is feasible and efficient for solving FE formulation for second-order hyperbolic equations.     

Modeling dendritic solidification of Al–3%Cu using cellular automaton and phase-field methods

We compared a cellular automaton (CA)–finite element (FE) model and a phase-field (PF)–FE model to simulate equiaxed dendritic growth during the solidification of cubic crystals. The equations of mass and heat transports were solved in the CA–FE model to calculate the temperature field, solute concentration, and the dendritic growth morphology. In the PF–FE model, a PF variable was used to identify solid and liquid phases and another PF variable was considered to determine the evolution of solute concentration. Application to Al–3.0 wt.% Cu alloy illustrates the capability of both CA–FE and PF–FE models in modeling multiple arbitrarily-oriented dendrites in growth of cubic crystals. Simulation results from both models showed quantitatively good agreement with the analytical model developed by Lipton–Glicksman–Kurz (LGK) in the tip growth velocity and the tip equilibrium liquid concentration at a given melt undercooling. The dendrite morphology and computational time obtained from the CA–FE model are compared to those of the PF–FE model and the distinct advantages of both methods are discussed.     

Fast algorithm for viscous Cahn-Hilliard equation

The main purpose of this paper is to solve the viscous Cahn-Hilliard equation via a fast algorithm based on the two time-mesh (TT-M) finite element (FE) method to ease the problem caused by strong nonlinearities. The TT-M FE algorithm includes the following main computing steps. First, a nonlinear FE method is applied on a coarse time-mesh τ_c. Here, the FE method is used for spatial discretization and the implicit second-order θ scheme (containing both implicit Crank-Nicolson and second-order backward difference) is used for temporal discretization. Second, based on the chosen initial iterative value, a linearized FE system on time fine mesh is solved, where some useful coarse numerical solutions are found by Lagrange’s interpolation formula. The analysis for both stability and a priori error estimates is made in detail. Numerical examples are given to demonstrate the validity of the proposed algorithm. Our algorithm is compared with the traditional Galerkin FE method and it is evident that our fast algorithm can save computational time.     

Toward a Hybrid-Trefftz element with a hole for elasto-plasticity?

The paper deals with the modelling of riveted assemblies for full-scale complete aircraft crashworthiness. Many comparisons between experiments and FE computations of bird impacts onto aluminium riveted panels have shown that macroscopic plastic strains were not sufficiently developed (and localised) in the riveted shell FE in the impact area. Consequently, FE models never succeed in initialising and propagating the rupture in the sheet metal plates and along rivet rows as shown by experiments, without calibrating the input data (especially the damage and failure properties of the riveted shell FE). To model the assembly correctly, it appears necessary to investigate on FE techniques such as Hybrid-Trefftz finite element method (H-T FEM). Indeed, perforated FE plates developed for elastic problems, based on a Hybrid-Trefftz formulation, have been found in the open literature. Our purpose is to find a way to extend this formulation so that the super-element can be used for crashworthiness. To reach this aim, the main features of an elastic Hybrid-Trefftz plate are presented and are then followed by a discussion on the possible extensions. Finally, the interpolation functions of the element are evaluated numerically.     

Finite element formulation based on proper orthogonal decomposition for parabolic equations

A proper orthogonal decomposition (POD) method is applied to a usual finite element (FE) formulation for parabolic equations so that it is reduced into a POD FE formulation with lower dimensions and enough high accuracy. The errors between the reduced POD FE solution and the usual FE solution are analyzed. It is shown by numerical examples that the results of numerical computations are consistent with theoretical conclusions. Moreover, it is also shown that this validates the feasibility and efficiency of POD method. This work was supported by National Natural Science Foundation of China (Grant Nos. 10871022, 10771065, and 60573158) and Natural Science Foundation of Hebei Province (Grant No. A2007001027)     

Sobre la necesidad de controlar el error de discretización de elementos finitos en optimización de forma estructural con algoritmos evolutivos

This work analyzes the influence of the discretization error contained in the Finite Element (FE) analyses of each design configuration proposed by the structural shape optimization algorithms over the behavior of the algorithm. The paper clearly shows that if FE analyses are not accurate enough, the final solution provided by the optimization algorithm will neither be optimal nor satisfy the constraints. The need for the use of adaptive FE analysis techniques in shape optimum design will be shown. The paper proposes the combination of two strategies to reduce the computational cost related to the use of mesh adaptivity in evolutionary optimization algorithms: (a) the use of the algorithm described by Bugeda et al. [1] which reduces the computational cost associated to the adaptive FE analysis of each geometrical configuration and, (b) the successive increase of the required accuracy of the FE analyses in order to obtain a considerable reduction of the computational cost in the early stages of the optimization process.     

A three-stage unsupervised dimension reduction method for text clustering

Dimension reduction is a well-known pre-processing step in the text clustering to remove irrelevant, redundant and noisy features without sacrificing performance of the underlying algorithm. Dimension reduction methods are primarily classified as feature selection (FS) methods and feature extraction (FE) methods. Though FS methods are robust against irrelevant features, they occasionally fail to retain important information present in the original feature space. On the other hand, though FE methods reduce dimensions in the feature space without losing much information, they are significantly affected by the irrelevant features. The one-stage models, FS/FE methods, and the two-stage models, a combination of FS and FE methods proposed in the literature are not sufficient to fulfil all the above mentioned requirements of the dimension reduction. Therefore, we propose three-stage dimension reduction models to remove irrelevant, redundant and noisy features in the original feature space without loss of much valuable information. These models incorporates advantages of the FS and the FE methods to create a low dimension feature subspace. The experiments over three well-known benchmark text datasets of different characteristics show that the proposed three-stage models significantly improve performance of the clustering algorithm as measured by micro F-score, macro F-score, and total execution time.