Linear Chebyshev approximation without Chebyshev sets

The provision of algorithms for computing best Chebyshev approximations on a continuum by general linear combinations of continuous functions is considered. Four possible approaches are described, and detailed comparisons are given for some test problems.AMS (MOS) subject classifications (1970). Primary 65D10; Secondary 41A50.     

Optimality and uniqueness conditions in complex rational Chebyshev approximation with examples

It is well known that best complex rational Chebyshev approximants are not always unique and that, in general, they cannot be characterized by the necessary local Kolmogorov condition or by the sufficient global Kolmogorov condition. Recently, Ruttan (1985) proposed an interesting sufficient optimality criterion in terms of positive semidefiniteness of some Hermitian matrix. Moreover, he asserted that this condition is also necessary, and thus provides a characterization of best approximants, in a fundamental case.In this paper we complement Ruttan's sufficient optimality criterion by a uniqueness condition and we present a simple procedure for computing the set of best approximants in case of nonuniqueness. Then, by exhibiting an approximation problem on the unit disk, we point out that Ruttan's characterization in the fundamental case is not generally true. Finally, we produce several examples of best approximants on a real interval and on the unit circle which, among other things, give some answers to open questions raised in the literature.     

Weighted simultaneous Chebyshev approximation

In this paper we discuss the problem of weighted simultaneous Chebyshev approximation to functions f₁,…f_m ε C(X) (1 m ∞), i.e., we wish to minimize the expression {∑^m_{j = 1} λ_j¦f_j − q¦^p}^1/p∞, where λ_j > 0, ∑^m_{j = 1} λ_j = 1, p 1. For this problem we establish the main theorems of the Chebyshev theory, which include the theorems of existence, alternation, de La Vallée Poussin, uniqueness, strong uniqueness, as well as that of continuity of the best approximation operator, etc.     

Adaptive bivariate Chebyshev approximation

We propose an adaptive algorithm which extends Chebyshev series approximation to bivariate functions, on domains which are smooth transformations of a square. The method is tested on functions with different degrees of regularity and on domains with various geometries. We show also an application to the fast evaluation of linear and nonlinear bivariate integral transforms. Work supported by the research project CPDA028291 “Efficient approximation methods for nonlocal discrete transforms” of the University of Padova, and by the GNCS-INdAM.     

GENERALIZED SIMULTANEOUS CHEBYSHEV APPROXIMATION

In this note,we develop,without assuming the Haar condition,a generalized simultaneousChebyshev approximation theory which is similar to the classical Chebyshev theory and con-rains it as a special case.Our results also contain those in[1]and[3]as a special case,and thetwo conjectures proposed by C.B.Dunham in[2]are proved to be true in the case of simulta-neous approximation.     

Chebyshev approximation by products

Characterization and uniqueness of minimax approximation by the product PQ of two finite dimensional subspaces P and Q is studied. Some approximants may have no standard characterization since PQ may not be a sun, but interior points do have the standard linear characterization.     

Lipschitz continuity of the best approximation operator in vector-valued Chebyshev approximation

When G is a finite dimensional Haar subspace of C(X,R^k), the vector-valued continuous functions (including complex-valued functions when k is 2) from a finite set X to Euclidean k-dimensional space, it is well-known that at any function f in C(X,R^k) the best approximation operator satisfies the strong unicity condition of order 2 and a Lipschitz (Hőlder) condition of order . This note shows that in fact the best approximation operator satisfies the usual Lipschitz condition of order 1.     

Chebyshev approximation of the null function by an affine combination of complex exponential functions

We describe the theoretical solution of an approximation problem that uses a finite weighted sum of complex exponential functions. The problem arises in an optimization model for the design of a telescope array occurring within optical interferometry for direct imaging in astronomy. The problem is to find the optimal weights and the optimal positions of a regularly spaced array of aligned telescopes, so that the resulting interference function approximates the zero function on a given interval. The solution is given by means of Chebyshev polynomials.     

Chebyshev approximation by exponential-polynomial sums

It is shown that best Chebyshev approximations by exponential-polynomial sums are characterized by (a variable number of) alternations of their error curve and are unique. Computation of best approximations via the Remez algorithm and Barrodale approach is considered.     

Weighted discrete nonlinear Chebyshev approximation

Modifications are given to let the discrete REMEZ program for nnlinear Chebyshev approximation handle weights.     

Convergence of interpolation in polynomial Chebyshev approximation

The quality of a polynomial approximation on an interval to a functionf is considered as a function of its points of interpolation. Iff satisfies a Lipschitz condition of order 1, the quality depends linearly on the distance of the points of interpolation from an optimal interpolating point set: further restrictions onf still give only linear dependence. This suggests that algorithms based on interpolation are inferior to algorithms based on error extrema (such as the Remes algorithm).