Comparison Theorems of Kolmogorov Type for Classes Defined by Cyclic Variation Diminishing Operators and Their Application

Presenting a unified approach, we establish a Kolmogorov-type comparison theorem for classes of 2π-periodic functions defined by a special class of operators having certain oscillation properties, which include the classical Sobolev class of 2π-periodic functions, the Achieser class, and the Hardy-Sobolev class as examples. Then, using these results, we prove a Taikov-type inequality, and calculate the exact values of the Kolmogorov, Gel'fand, linear, and information n-widths of these classes of functions in the space L_q, which is the classical Lebesgue integral space of 2π-periodic functions with the usual norm.     

Fractional Derivatives and Best Approximation

We relate fractional derivatives of some operators to the rate of best approximation from a space of eigenfunctions of those operators. This is done via the introduction of "fractional" K-functionals and appropriate Riesz means. Continuous simultaneous approximations and fractional Kolmogorov-type inequalities are also achieved.     

Weighted Best Local Approximation

In this survey, the notion of a balanced best multipoint local approximation is fully exposed since they were treated in the Lpspaces and recent results in Orlicz spaces. The notion of balanced point, which was introduced by Chui et al. in 1984 are extensively used.     

Near Best Tree Approximation

Tree approximation is a form of nonlinear wavelet approximation that appears naturally in applications such as image compression and entropy encoding. The distinction between tree approximation and the more familiar n-term wavelet approximation is that the wavelets appearing in the approximant are required to align themselves in a certain connected tree structure. This makes their positions easy to encode. Previous work [4,6] has established upper bounds for the error of tree approximation for certain (Besov) classes of functions. This paper, in contrast, studies tree approximation of individual functions with the aim of characterizing those functions with a prescribed approximation error. We accomplish this in the case that the approximation error is measured in L ₂, or in the case p2, in the Besov spaces B _p ⁰(L _p ), which are close to (but not the same as) L _p . Our characterization of functions with a prescribed approximation order in these cases is given in terms of a certain maximal function applied to the wavelet coefficients.     

联合最佳逼近

本文研究了二元函数用紧Hausdorff空间上的连续函数集的联合逼近问题,建立了包括特征定理、唯一性定理、强唯一性定理和dela Vallée Poussin定理在内的Chebyshev逼近理论。给出了求解最佳逼近元的Remes型第一算法和两种一般的简化方法。     

Average Best m-term Approximation

We introduce the concept of average best m-term approximation widths with respect to a probability measure on the unit ball or the unit sphere of $\ell_{p}^{n}$ . We estimate these quantities for the embedding $id:\ell_{p}^{n}\to\ell_{q}^{n}$ with 0<p??q??? for the normalized cone and surface measure. Furthermore, we consider certain tensor product weights and show that a typical vector with respect to such a measure exhibits a strong compressible (i.e., nearly sparse) structure. This measure may therefore be used as a random model for sparse signals.     

Weighted Best Local Approximation

In this survey the notion of a balanced best multipoint local approximation is fully exposed since they were treated in the Lp spaces and recent results in Orlicz spaces.The notion of balanced point,introduced by Chui et al.in 1984 are extensively used.     

On Best Simultaneous Approximation

The problem is considered of best approximation of finite number of functions simultaneously. For a very general class of norms, characterization results are derived. The main part of the paper is concerned with proving uniqueness and strong uniqueness theorems. For a particular subclass, which includes the important special case of the Chebyshev norm, a characterization is given of a uniqueness element.     

近严格凸与最佳逼近

本文研究近严格凸与最佳逼近的关系．证明了Ｂａｎａｃｈ空间Ｘ是近严格凸的当且仅当Ｘ的每个子空间是紧－半－切比晓夫空间．     

Common Fixed Points and Best Approximation

We prove a common fixed-point theorem generalizing results of Dotson and Habiniak. Using this result, we extend, generalize, and unify well known results on fixed points and common fixed points of best approximation.     

Generalized Deviations and Best Approximation Theory

ABSTRACT

Given the importance of standard deviation in applications, we think that it is worthwhile considering other types of deviations. For this purpose, we introduce a generalization of the concept of deviation. We also introduce a new definition for the concept of generalized mean. We then highlight the connection that exists between arithmetic mean, standard deviation, and best approximation, and we establish necessary and sufficient conditions that would guarantee the existence of similar connections between generalized means, generalized deviations, and best approximation. We finish by presenting some open problems.     

Best Approximation with Walsh Atoms

We consider the approximation in L ² R of a given function using finite linear combinations of Walsh atoms, which are Walsh functions localized to dyadic intervals, also called Haar—Walsh wavelet packets. It is shown that up to a constant factor, a linear combination of K atoms can be represented to relative error ɛ by a linear combination of orthogonal atoms. In finite dimension N, best approximation with K orthogonal atoms can be realized with an algorithm of order . A faster algorithm of order solves the problem with indirect control over K. Therefore the above result connects algorithmic and theoretical best approximation. Date received: July 6, 1995. Date revised: January 8, 1996.     

Best Approximation with Coefficient Constraints

For given = (₁,..., _n) and ß = (ß₁,...,ß_n), with – _i < ß_i (i = 1, ...,n) and continuous functions u₁,...,u_n, set This paper is concerned with best approximating continuous functions,in the uniform norm, from U(; ß). We exactly characterizethe u₁,..., u_n for which the best approximant to every continuousfunction is unique. We also present a general theorem characterizingall best approximants. When (u₁,..., u_n) is a Descartes, ora weak Descartes, system on [0, 1], explicit characterizationsof the best approximants in terms of equioscillations are given.These results are applied to spline spaces. They are also usedto complete the characterizations in certain specific examplespreviously considered in the literature.     

最佳混合范数逼近

最佳混合范数逼近@王建东...     

Best Approximation in Numerical Radius

Let X be a reflexive Banach space. In this article, we give a necessary and sufficient condition for an operator T ∈ 𝒦(X) to have the best approximation in numerical radius from the convex subset 𝒰 ? 𝒦(X), where 𝒦(X) denotes the set of all linear, compact operators from X into X. We also present an application to minimal extensions with respect to the numerical radius. In particular, some results on best approximation in norm are generalized to the case of the numerical radius.     

Polyharmonic and Related Kernels on Manifolds: Interpolation and Approximation

This article is devoted to developing a theory for effective kernel interpolation and approximation in a general setting. For a wide class of compact, connected C ^∞ Riemannian manifolds, including the important cases of spheres and SO(3), and using techniques involving differential geometry and Lie groups, we establish that the kernels obtained as fundamental solutions of certain partial differential operators generate Lagrange functions that are uniformly bounded and decay away from their center at an algebraic rate, and in certain cases, an exponential rate. An immediate corollary is that the corresponding Lebesgue constants for interpolation as well as for L ₂ minimization are uniformly bounded with a constant whose only dependence on the set of data sites is reflected in the mesh ratio, which measures the uniformity of the data. The kernels considered here include the restricted surface splines on spheres, as well as surface splines for SO(3), both of which have elementary closed-form representations that are computationally implementable. In addition to obtaining bounded Lebesgue constants in this setting, we also establish a “zeros lemma” for domains on compact Riemannian manifolds—one that holds in as much generality as the corresponding Euclidean zeros lemma (on Lipschitz domains satisfying interior cone conditions) with constants that clearly demonstrate the influence of the geometry of the boundary (via cone parameters) as well as that of the Riemannian metric.     

Minimization and Best Approximation(II)

This paper similar to the previous work^[6] is to discuss independently the problem of minimization of a functional $\Psi(P)=\int_X {F(x,P(x))dx}$in a subset of the space L(X).We have likewise established the concerned theorems of existence,characterization and uniqueness.The results herein may effectively be applied to a number of problems of approximation,especially to those of simultaneous approximation.     

Orlicz-Sobolev空间单调性及其在最佳逼近中的应用

改进了Hudzik,Kurc关于最佳逼近中的结果,给出了赋Orlicz范数的Orlicz- Sobolev空间具有一致单调性、局部一致单调性和严格单调性的充要条件、单调系数的数值,以及在最佳逼近中的应用.     

Cp Condition and the Best Local Approximation

In this paper, we introduce a condition weaker than the Lpdifferentiability,which we call Cpcondition. We prove that if a function satisfies this condition at a point, then there exists the best local approximation at that point. We also give a necessary and sufficient condition for that a function be Lpdifferentiable. In addition, we study the convexity of the set of cluster points of the net of best appoximations of f,{Pe( f)} as e → 0.