Unconstrained and convex polynomial approximation inC[−1,1]

Some estimates for unconstrained and convex polynomial approximation in the uniform metric are obtained. These results are given in terms of the Ditzian-Totik moduli of smoothness , ≤1 with . The construction of the approximating polynomials does not depend on λ.     

Shape-preserving bivariate polynomial approximation inC([−1,1]×[−1,1])

In this paper we construct bivariate polynomials attached to a bivariate function, that approximate with Jackson-type rate involving a bivariate Ditzian-Totik ω2-modulus of smoothness and preserve some natural kinds of bivariate monotonicity and convexity of function.The result extends that in univariate case-of D. Leviatan in [5-6], improves that in bivariate case of the author in [3] and in some special cases, that in bivariate case of G. Anastassiou in [1].     

A discrepancy theorem concerning polynomials of best approximation inL w p [−1, 1]

Letw be a suitable weight function,B _n,p denote the polynomial of best approximation to a functionf inL _w ^p [–1, 1],v _n be the measure that associates a mass of 1/(n+1) with each of then+1 zeros ofB _n+1,p–B _n,p and be the arcsine measure defined by . We estimate the rate at which the sequencev _n converges to in the weak-^* topology. In particular, our theorem applies to the zeros of monic polynomials of minimalL _w ^p norm.This author gratefully acknowledges partial support from NSA contract #A4235802 during 1992, AFSOR Grant 226113 during 1993 and The Alexander von Humboldt Foundation during both of these years.     

Interpolating polynomial wavelets on [−1,1]

The present paper gives a contribution of wavelet aspects to classical algebraic polynomial approximation theory. As is so often the case in classical approximation, the authors follow the pattern provided by the trigonometric polynomial case. Algebraic polynomial interpolating scaling functions and wavelets are constructed by using the interpolation properties of de la Vallée Poussin kernels with respect to the four kinds of Chebyshev weights. For the decomposition and reconstruction of a given function the structure of the involved matrices is studied in order to reduce the computational effort by means of fast discrete cosine and sine transforms. Dedicated to Prof. Guiseppe Mastroianni on the occasion of his 65th birthday.AMS subject classification 65D05, 65T60     

Convex polynomial and spline approximation in C[−1, 1]

We prove that a convex functionf C[–1, 1] can be approximated by convex polynomialsp _n of degreen at the rate of ₃(f, 1/n). We show this by proving that the error in approximatingf by C² convex cubic splines withn knots is bounded by ₃(f, 1/n) and that such a spline approximant has anL third derivative which is bounded by n³₃(f, 1/n). Also we prove that iff C²[–1, 1], then it is approximable at the rate ofn ^–2 (f, 1/n) and the two estimates yield the desired result.Communicated by Ronald A. DeVore.     

Asymptotics of Orthogonal Polynomials for a Weight with a Jump on [?1,1]

We consider the orthogonal polynomials on [−1,1] with respect to the weight

Polynomials of least deviation from zero in the L[−1, 1] metric with five fixed coefficients

We study properties of polynomials R _n+5(x) of least deviation from zero in the L[?1, 1] metric, with five given leading coefficients whose forms were calculated previously. Theorems 1 and 2 together with Theorem A contain, in particular, a final classification of polynomials R _n+5(x) that have exactly (n + 1) sign changes in (?1, 1).     

The best one-sided approximation of the classes WrHω

In this paper we calculate the upper bounds of the best one-sided approximations, by trigonometric polynomials and splines of minimal defect in the metric of the space L, of the classes W^rH (r = 2, 4, 6, ...) of all 2-periodic functions f(x) that are continuous together with their r-th derivative f^r(x) and such that for any points x and x we have ¦f ^r (x) f^r (x) ¦ (x–x¦), where (t) is a modulus of continuity that is convex upwards.Translated from Matematicheskie Zametki, Vol. 21, No. 3, 313–327, March, 1977.     

On zeros of polynomials of best approximation to holomorphic andC ∞ functions

LetE be a compact subset of the complex planeC such that Leja's extremal functionL _E forE is continuous. If almost all zeros of the polynomials of best approximation to a functionfC(E) are outside the setE _R ={zC:L _E (z<R)}, for someR>1, thenf is extendible to a holomorphic function inE _R . If the zeros ofn-th, polynomial of best approximation tof are outside and the sequence {R _n ^–n } rapidly decreases to zero thenf can be extended to aC function on 075-4}.     

Zolotarev's first problem — the best approximation by polynomials of degree ≤n − 2 tox n − nσx n−1 in [−1, 1]

Chebyshev determined $$\mathop {\min }\limits_{(a)} \mathop {\max }\limits_{ - 1 \le x \le 1} |x^n + a_1 x^{n - 1} + \cdots + a_n |$$ as 2^1?n , which is attained when the polynomial is 2^1?n T _n(x), whereT _n(x) = cos(n arc cosx). Zolotarev's First Problem is to determine $$\mathop {\min }\limits_{(a)} \mathop {\max }\limits_{ - 1 \le x \le 1} |x^n - n\sigma x^{n - 1} + a_2 x^{n - 2} + \cdots + a_n |$$ as a function ofn and the parameter σ and to find the extremal polynomials. He solved this in 1878. Another discussion was given by Achieser in 1928, and another by Erdös and Szegö in 1942. The case when 0≤|σ|≤ tan²(π/2n) is quite simple, but that for |σ|> tan²(π/2n) is quite different and very complicated. We give two new versions of the proof and discuss the change in character of the solution. Both make use of the Equal Ripple Theorem.     

Some numerical results on best uniform rational approximation ofx α on [0,1]

Let be a positive number, and letE _n,n (x ;[0,1]) denote the error of best uniform rational approximation from _n,n tox on the interval [0,1]. We rigorously determined the numbers {E _n,n (x ;[0,1])} _n ^=1/30 for six values of in the interval (0, 1), where these numbers were calculated with a precision of at least 200 significant digits. For each of these six values of , Richardson's extrapolation was applied to the products to obtain estimates of

Approximation of analytic functions by polynomials “close” to polynomials of best approximation

The rate of approximation of analytic functions at interior points of compact sets with connected complement by polynomials close to polynomials of best approximation is investigated.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 44, No. 2, pp. 208–214, February, 1992.     

On estimating the rate of best trigonometric approximation by a modulus of smoothness

Best trigonometric approximation in L _p , 1≦p≦∞, is characterized by a modulus of smoothness, which is equivalent to zero if the function is a trigonometric polynomial of a given degree. The characterization is similar to the one given by the classical modulus of smoothness. The modulus possesses properties similar to those of the classical one.     

Proximal primal–dual best approximation algorithm with memory

We propose a new modified primal–dual proximal best approximation method for solving convex not necessarily differentiable optimization problems. The novelty of the method relies on introducing memory by taking into account iterates computed in previous steps in the formulas defining current iterate. To this end we consider projections onto intersections of halfspaces generated on the basis of the current as well as the previous iterates. To calculate these projections we are using recently obtained closed-form expressions for projectors onto polyhedral sets. The resulting algorithm with memory inherits strong convergence properties of the original best approximation proximal primal–dual algorithm. Additionally, we compare our algorithm with the original (non-inertial) one with the help of the so called attraction property defined below. Extensive numerical experimental results on image reconstruction problems illustrate the advantages of including memory into the original algorithm.     

On the relations among best approximation and Fourier coeffcients

We discuss the relations among the best approximation En(f) and the Fourier coeffcients of a function, f(n) ∈ C,n = 0,±1,±2,..., under the conditions that {f (n)}∞n=0 ∈ MVBVS* and {f (n) f(n)}∞n=0 ∈ MVBVS*, where MVBVS* is the class of the so-called Strong Mean Value Bounded Variation Sequences.     

Approximation of Sondow’s generalized-Euler-constant function on the interval [−1, 1]

Using the Euler-Maclaurin (Boole/Hermite) summation formula, the generalized-Euler-Sondow-constant function γ(z),

$ \gamma(z):=\sum_{k=1}^{\infty}z^{k-1}\left(\frac{1}{k}-\ln\frac{k+1}{k}\right) \qquad (-1\le z\le 1),$

where \({\gamma(-1)=\ln\frac{4}{\pi}}\) and γ(1) is the Euler-Mascheroni constant, is estimated accurately.

     

Approximation Properties of Julia Polynomials

Let G be a finite simply connected domain in the complex plane C, bounded by a rectifiable Jordan curve L, and let w = φ0 （z） be the Riemann conformal mapping of G onto D （0, r0） ：= {E-mail： ： ｜｜ 〈 r0}, normalized by the conditions φ0 （z0） = 0, φ＇0 （z0） = 1. In this work, the rate of approximation of φ0 by the polynomials, defined with the help of the solutions of some extremal problem, in a closed domain G is studied. This rate depends on the geometric properties of the boundary L.     

The computation of a best monotone L p approximation for 1 ≤ p < ∞

An algorithm for the computation of a best monotone L _p approximate 1≤p<∞ is presented and its convergence theorems are established.