Approximation of Parametric Derivatives by the Empirical Interpolation Method

We introduce a general a priori convergence result for the approximation of parametric derivatives of parametrized functions. We consider the best approximations to parametric derivatives in a sequence of approximation spaces generated by a general approximation scheme, and we show that these approximations are convergent provided that the best approximation to the function itself is convergent. We also provide estimates for the convergence rates. We present numerical results with spaces generated by a particular approximation scheme—the Empirical Interpolation Method—to confirm the validity of the general theory.     

On the existence of a measurable function with given values of the best approximations inL 0

In the space of convergence in measure, we study the Bernstein problem of existence of a function with given values of the best approximations by a system of finite-dimensional subspaces strictly imbedded in one another.     

On the global convergence of trust region algorithms for unconstrained minimization

Many trust region algorithms for unconstrained minimization have excellent global convergence properties if their second derivative approximations are not too large [2]. We consider how large these approximations have to be, if they prevent convergence when the objective function is bounded below and continuously differentiable. Thus we obtain a useful convergence result in the case when there is a bound on the second derivative approximations that depends linearly on the iteration number.     

Approximation of nonnegative functions by means of exponentiated trigonometric polynomials

We consider the problem of approximating a nonnegative function from the knowledge of its first Fourier coefficients. Here, we analyze a method introduced heuristically in a paper by Borwein and Huang (SIAM J. Opt. 5 (1995) 68–99), where it is shown how to construct cheaply a trigonometric or algebraic polynomial whose exponential is close in some sense to the considered function. In this note, we prove that approximations given by Borwein and Huang's method, in the trigonometric case, can be related to a nonlinear constrained optimization problem, and their convergence can be easily proved under mild hypotheses as a consequence of known results in approximation theory and spectral properties of Toeplitz matrices. Moreover, they allow to obtain an improved convergence theorem for best entropy approximations.     

Computation of Best Simultaneous Approximations with a Singularity

Simultaneous approximation errors are generally discontinuous when the function to be approximated contains a zero in its domain of definition. In this article we indicate how the presence of such a zero (or, equivalently, the resulting singularity in the error expression) affects the computational schemata for finding all the best approximations. In particular, we develop an algorithm and show that its convergence rate is “best possible expected” in the sense that it is quadratic, as in the case for continuous errors. Numerical examples are provided.     

Functions with prescribed best linear approximations

A common problem in applied mathematics is that of finding a function in a Hilbert space with prescribed best approximations from a finite number of closed vector subspaces. In the present paper we study the question of the existence of solutions to such problems. A finite family of subspaces is said to satisfy the Inverse Best Approximation Property (IBAP) if there exists a point that admits any selection of points from these subspaces as best approximations. We provide various characterizations of the IBAP in terms of the geometry of the subspaces. Connections between the IBAP and the linear convergence rate of the periodic projection algorithm for solving the underlying affine feasibility problem are also established. The results are applied to investigate problems in harmonic analysis, integral equations, signal theory, and wavelet frames.     

Minimum relative error approximations for 1/t

Summary We give explicit solutions to the problem of minimizing the relative error for polynomial approximations to 1/t on arbitrary finite subintervals of (0, ). We give a simple algorithm, using synthetic division, for computing practical representations of the best approximating polynomials. The resulting polynomials also minimize the absolute error in a related functional equation. We show that, for any continuous function with no zeros on the interval of interest, the geometric convergence rates for best absolute error and best relative error approximants must be equal. The approximation polynomials for 1/t are useful for finding suitably precise initial approximations in iterative methods for computing reciprocals on computers.     

Positive Sampling in Wavelet Subspaces

This paper is devoted to the discussion of a “hybrid” sampling series, a series of translates of a nonnegative summability function used in place of an orthogonal scaling function. The coefficients in the series are taken to be sampled values of the function to be approximated. This enables one to avoid the integration which arises in the other series. The approximations based on this hybrid series have certain desirable convergence properties: they are locally uniformly convergent for locally continuous functions, they have quadratic uniform convergence rate for functions in certain Sobolev spaces, they are locally bounded when the function is locally bounded and therefore, in particular, Gibbs' phenomenon is avoided. Numerical experiments are given to illustrate the theoretical results and to compare these approximations with the scaling function approximations.     

Approximation of Multiple Stratonovich Fractional Integrals

Abstract

We study multiple Riemann-Stieltjes integral approximations to multiple Stratonovich fractional integrals. Two standard approximations (Wong-Zakai and Mollifier approximations) are considered and we show the convergence in the mean square sense and uniformly on compact time intervals of these approximations to the multiple Stratonovich fractional integral.     

Distribution of alternation points in best rational approximations

We study the convergence of counting measures of alternation point sets in best rational approximations to the equilibrium measure. It is shown that, for any prescribed nondecreasing sequence of denominator degrees, there exists a function analytic on [0, 1] and a sequence of numerator degrees such that the corresponding sequence of measures does not converge to the equilibrium measure of the interval.     

Some notes on approximation of logarithms

Joint rational approximations to a collection of logarithms with a common denominator are considered. In this case each function is approximated at its zero. The asymptotic behavior of approximations is completely described in the real case of two logarithms, convergence of approximations is also investigated. A theoretic-potential interpretation is proposed.     

On certain order constrained Chebyshev rational approximations

Some rational approximations which share the properties of Padé and best uniform approximations are considered. The approximations are best in the Chebyshev sense, but the optimization is performed over subsets of the rational functions which have specified derivatives at one end point of the approximation interval. Explicit relationships between the Padé and uniform approximations are developed assuming the function being approximated satisfies easily verified constraints. The results are applied to the exponential function to determine the existence of best uniform A-acceptable approximations.     

Best approximation and moduli of smoothness: Computation and equivalence theorems

In this paper we investigate the trigonometric series with the β-general monotone coefficients. First, we study the uniform convergence criterion. The estimates of best approximations and moduli of smoothness of the series in uniform metrics are obtained in terms of coefficients. These results imply several important relations between moduli of smoothness of different orders (in particular, Marchaud-type inequality) and best approximations.     

A Lax equivalence theorem for stochastic differential equations

In this paper, a stochastic mean square version of Lax’s equivalence theorem for Hilbert space valued stochastic differential equations with additive and multiplicative noise is proved. Definitions for consistency, stability, and convergence in mean square of an approximation of a stochastic differential equation are given and it is shown that these notions imply similar results as those known for approximations of deterministic partial differential equations. Examples show that the assumptions made are met by standard approximations.     

Continuous selections and convergence of best Lp –approximations in subspaces of spline functions

The chief purpose of this paper is to study the problem of existence of continuous selections for the metric projection and of convergence of best L_p–approximations in subspaces of polynomial spline functions defined on a real compact interval I. Nürnberger-Sommer [8] have shown that there exists a continuous selection s if and only if the numberof knots k is less than or equal to the order m of the splines. Using their construction of s the author [12] has proved that the sequence of best L_p–approximations of f converges to s(f) as ρ→∞ for every continuous function f. The main results of this paper say that also in the case when k>m there exists always a continuous selection s (it is even pointwise-Lipschitz-continuous and quasi-linear) provided that the approximation problem is restricted to certain subsets I_epsilon; of I. In addition it is shown that anologously as for k≤m the sequence of best L_papproximations of f converges to s(f) for every continuous function f on Iε     

一种扰动的序列二次规划算法及其全局收敛性

其中r_i 是 m 维扰动向量.代替Q(x_i,H_i),那么算法的收敛性及其收敛率如何受到r_i 影响的问题,并指出还没有看到在这方面的工作.本文对这个问题进行了探讨,将[2]提出的算法用于 r_i(?)0的情形,在适当选择步长的条件下,得到了全局收敛性.由于在计算机上计算 g(x_k)+▽g(x_k)~T(x—x_k)时会有误差,我们可以将此误差视为本文中的 r_k,因而这种讨论是必要的.     

最优分段逼近的几个迭代算法及其收敛性

本文给出了最优分段逼近的几类迭代算法,并从理论上证明它们对于任意初始条件都收敛到唯一的最优逼近.在电子计算机上进行了计算,表明效果良好.文末给出一些数值例子.     

Convergence rate of multiple fractional Stratonovich type integral for Hurst parameter less than 1/2

In this paper, we have investigated the problem of the convergence rate of the multiple integralwhere f ∈ Cn+1([0, T ]n) is a given function, π is a partition of the interval [0, T ] and {BtHi ,π} is a family of interpolation approximation of fractional Brownian motion BtH with Hurst parameter H < 1/2. The limit process is the multiple Stratonovich integral of the function f . In view of known results, the convergence rate is different for different multiplicity n. Under some mild conditions, we obtain that the uniform convergence rate is 2H in the mean square sense, where is the norm of the partition generating the approximations.     

A least squares method for finding the preisach hysteresis operator from measurements

Summary A finite element like least squares method is introduced for determining the density function in the Preisach hysteresis model from overdeterined measured data. It is shown that the least squares error depends on the quality of the data and the best approximations to the analytic density. For consistent data criteria are given for convergence of the approximate density and Preisach operator with increasing measurements.Dedicated to Günther Hämmerlin on the occasion of his 60th birthday     

On Double Stratonovich Fractional Integrals and Some Strong and Weak Approximations

Abstract

Double Stratonovich integrals with respect to the odd part and even part of the fractional Brownian motion are constructed. The first and the second moments of such integrals are explicitly identified. As application of double Stratonovich integrals a strong law of large numbers for efBm and ofBm is derived.

Riemann–Stieltjes integral approximations to double Stratonovich fractional integrals are also considered. The strong convergence (almost surely and mean square) is obtained for approximations based on explicit series expansions of the fractional Brownian processes. The weak convergence is derived for approximations by processes with absolutely continuous paths which converge weakly to the considered fractional Brownian processes. The above-mentioned convergences are obtained for deterministic integrands which are given by bimeasures.