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One of the basic principles of Approximation Theory is that the quality of approximations increase with the smoothness of the function to be approximated. Functions that are smooth in certain subdomains will have good approximations in…

Numerical Analysis · Mathematics 2016-12-23 Licia Lenarduzzi , Robert Schaback

Feedforward neural networks have wide applicability in various disciplines of science due to their universal approximation property. Some authors have shown that single hidden layer feedforward neural networks (SLFNs) with fixed weights…

Neural and Evolutionary Computing · Computer Science 2018-01-04 Namig J. Guliyev , Vugar E. Ismailov

Many problems of theoretical and practical interest involve finding an optimum over a family of convex functions. For instance, finding the projection on the convex functions in $H^k(\Omega)$, and optimizing functionals arising from some…

Numerical Analysis · Mathematics 2008-04-11 Néstor E. Aguilera , Pedro Morin

We introduce another new type of combinations of Bernstein operators in this paper, which can be used to approximate the functions with inner singularities. The direct and inverse results of the weighted approximation of this new type…

Functional Analysis · Mathematics 2011-06-28 Wen-ming Lu , Lin Zhang

This article establishes a complete approximate axiomatization for the real-closed field $\mathbb{R}$ expanded with all differentially-defined functions, including special functions such as $\sin(x), \cos(x), e^x, \dots$. Every true…

Logic in Computer Science · Computer Science 2025-06-11 André Platzer , Long Qian

In this paper we consider class of continuous functions, called quasiaharmonic functions, admitting best approximations by harmonic polynomials. In this class we prove a uniqueness theorem by analogy with the analytic functions.

Complex Variables · Mathematics 2013-02-21 S. A. Imomkulov , Z. Sh. Ibragimov

In this paper, we derive optimality conditions (Chebyshev approximation) for multivariate functions. The theory of Chebyshev (uniform) approximation for univariate functions is very elegant. The optimality conditions are based on the notion…

Optimization and Control · Mathematics 2015-10-22 Nadezda Sukhorukova , Julien Ugon , David Yost

The problem of recovering a moment-determinate multivariate function $f$ via its moment sequence is studied. Under mild conditions on $f$, the point-wise and $L_1$-rates of convergence for the proposed constructions are established. The…

Statistics Theory · Mathematics 2023-12-08 Robert Mnatsakanov , Rafik Aramyan , Farhad Jafari

This paper considers binomial approximation of continuous time stochastic processes. It is shown that, under some mild integrability conditions, a process can be approximated in mean square sense and in other strong metrics by binomial…

Computational Finance · Quantitative Finance 2015-02-09 Nikolai Dokuchaev

We prove that univalent harmonic mappings can be approximated by univalent Fourier series of step functions.

Complex Variables · Mathematics 2024-04-24 Allen Weitsman

We discuss technical results on learning function approximations using piecewise-linear basis functions, and analyze their stability and convergence using nonlinear contraction theory.

Optimization and Control · Mathematics 2018-04-27 Winfried Lohmiller , Philipp Gassert , Jean-Jacques Slotine

For convex univalent functions we give instances where the sharp bound for various coefficient functionals are identical to those for the corresponding bound for the inverse function. We give instances where the sharp bounds differ and also…

Complex Variables · Mathematics 2022-12-12 Derek K. Thomas

In this paper, a technique on constructing nonlinear resilient Boolean functions is described. By using several sets of disjoint spectra functions on a small number of variables, an almost optimal resilient function on a large even number…

Information Theory · Computer Science 2009-11-18 WeiGuo Zhang , GuoZhen Xiao

In this short, conceptual paper we observe that essentially the same mathematics applies in three contexts with disparate literatures: (1) sigmoidal and RBF approximation of smooth functions, (2) rational approximation of analytic functions…

Numerical Analysis · Mathematics 2023-03-06 Daan Huybrechs , Lloyd N. Trefethen

Cain, Clark and Rose defined a function $f\colon \RR^n \to \RR$ to be \emph{vertically rigid} if $\graph(cf)$ is isometric to $\graph (f)$ for every $c \neq 0$. It is \emph{horizontally rigid} if $\graph(f(c \vec{x}))$ is isometric to…

Classical Analysis and ODEs · Mathematics 2011-09-23 Richárd Balka , Márton Elekes

A function in a class $\mathcal{F}(X)$ is said to be subdifferentially determined in $\mathcal{F}(X)$ if it is equal up to an additive constant to any function in $\mathcal{F}(X)$ with the same subdifferential. A function is said to be…

Optimization and Control · Mathematics 2018-10-16 Marc Lassonde

It is a natural question to ask which plurisubharmonic functions admit a 'nice' approximation in the sense of a decreasing equisingular approximation with analytic singularities. For arbitrary toric plurisubharmonic functions, we give a…

Complex Variables · Mathematics 2022-02-25 Jongbong An , Hoseob Seo

We consider the problem of determining, given x, y in Z^k and a finite set F of affine functions on Z^k, whether y is reachable from x by applying the functions F. We also consider the analogous problem over N^k. These problems are known to…

Formal Languages and Automata Theory · Computer Science 2013-04-10 Daniel Fremont

We present a constructive proof of Brouwer's fixed point theorem for uniformly continuous and sequentially locally non-constant functions based on the existence of approximate fixed points. And we will show that Brouwer's fixed point…

Logic · Mathematics 2011-08-24 Yasuhito Tanaka

In this paper we introduce and study a class of structured set-valued operators which we call union averaged nonexpansive. At each point in their domain, the value of such an operator can be expressed as a finite union of single-valued…

Optimization and Control · Mathematics 2020-04-06 Minh N. Dao , Matthew K. Tam