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We consider nonconvex real valued functions whose truncations are either quasiconvex or even convex starting with a certain level. Among them, the $C^2$-smooth functions whose level sets are all completely contained in the positive definite…

Classical Analysis and ODEs · Mathematics 2026-03-05 Cornel Pintea

A deep approximation is an approximating function defined by composing more than one layer of simple functions. We study deep approximations of functions of one variable using layers consisting of low-degree polynomials or simple conformal…

Numerical Analysis · Mathematics 2025-04-25 Kingsley Yeon

In the field of radial basis functions mathematicians have been endeavouring to find infinitely differentiable and compactly supported radial functions. This kind of functions are extremely important for some reasons. First, its…

Numerical Analysis · Mathematics 2007-05-23 Lin-Tian Luh

We consider a countably generated and uniformly closed algebra of bounded functions. We assume that there is a lower semicontinuous, with respect to the supremum norm, quadratic form and that normal contractions operate in a certain sense.…

Functional Analysis · Mathematics 2018-06-29 Michael Hinz , Alexander Teplyaev

We prove some results on when functions on compact sets $K \subset \mathbb C$ can be approximated by polynomials avoiding values in given sets. We also prove some higher dimensional analogues. In particular we prove that a continuous…

Classical Analysis and ODEs · Mathematics 2021-08-17 Johan Andersson

The total loss function associated with a set of cross-sectional predictions, that is, estimates or forecasts, summarizes the set's overall accuracy. Its arguments are the individual cross-sectional units' loss functions. Under general…

Methodology · Statistics 2025-07-22 Charles D. Coleman

For any pair of bounded observables $A$ and $B$ with pure point spectra, we construct an associated "joint observable" which gives rise to a notion of a joint (projective) measurement of $A$ and $B$, and which conforms to the intuition that…

Quantum Physics · Physics 2015-06-22 Richard DeJonghe , Kimberly Frey , Tom Imbo

We consider the approximation of a continuous function, defined on a compact set of the $d$-dimensional Euclidean space, by sums of two ridge functions. We obtain a necessary and sufficient condition for such a sum to be a best…

Functional Analysis · Mathematics 2016-09-28 Vugar Ismailov

Let $N$ be a positive integer. We say a non-constant rational function $U(x)\in{\mathbb C}(x)$ is $N$-\emph{unital} if all the zeros and poles of both $U(x)$ and $1-U(x)$ are either 0 or $N$-th roots of unity. These functions are called…

Number Theory · Mathematics 2022-05-03 Jianqiang Zhao

We study the mean-value harmonic functions on open subsets of $\mathbb{R}^n$ equipped with weighted Lebesgue measures and norm induced metrics. Our main result is a necessary condition saying that all such functions solve a certain…

Analysis of PDEs · Mathematics 2018-12-11 Antoni Kijowski

A key problem in approximation theory is the recovery of high-dimensional functions from samples. In many cases, the functions of interest exhibit anisotropic smoothness, and, in many practical settings, the nature of this anisotropy may be…

Numerical Analysis · Mathematics 2026-04-10 Ben Adcock , Avi Gupta

In a previous paper [Adcock & Huybrechs, 2019] we described the numerical approximation of functions using redundant sets and frames. Redundancy in the function representation offers enormous flexibility compared to using a basis, but…

Numerical Analysis · Mathematics 2020-07-13 Ben Adcock , Daan Huybrechs

Continuous functions on the unit interval are relatively tame from the logical and computational point of view. A similar behaviour is exhibited by continuous functions on compact metric spaces equipped with a countable dense subset. It is…

Logic · Mathematics 2025-01-29 Sam Sanders

We investigate a class of composite nonconvex functions, where the outer function is the sum of univariate extended-real-valued convex functions and the inner function is the limit of difference-of-convex functions. A notable feature of…

Optimization and Control · Mathematics 2024-11-21 Hanyang Li , Ying Cui

Reconstructing a band-limited function from its finite sample data is a fundamental task in signal analysis. A Gaussian regularized Shannon sampling series has been proved to be able to achieve exponential convergence for uniform sampling.…

Signal Processing · Electrical Eng. & Systems 2022-10-10 Yunfei Yang , Haizhang Zhang

The familiar cascade measures are sequences of random positive measures obtained on $[0,1]$ via $b$-adic independent cascades. To generalize them, this paper allows the random weights invoked in the cascades to take real or complex values.…

Probability · Mathematics 2010-10-22 Julien Barral , Xiong Jin , Beno\^{ı}t Mandelbrot

In this paper we introduce two conceptual algorithms for minimising abstract convex functions. Both algorithms rely on solving a proximal-type subproblem with an abstract Bregman distance based proximal term. We prove their convergence when…

Optimization and Control · Mathematics 2026-01-09 Reinier Díaz Millán , Julien Ugon

We consider continuous functions f : [0,1] \to R that cut the real axis at every point of a measurable set of positive measure and we construct examples where f fails to have bounded variation, and at the opposite end, where f admits…

Classical Analysis and ODEs · Mathematics 2015-03-19 Omid Zabeti

Finite differences have been widely used in mathematical theory as well as in scientific and engineering computations. These concepts are constantly mentioned in calculus. Most frequently-used difference formulas provide excellent…

Numerical Analysis · Mathematics 2010-06-09 Brian Jain , Andrew D. Sheng

Let n points be taken at random on a circle of unit circumference and clockwise ordered. Uniform spacings are defined as the clockwise arc-lengths between the successive points from this sample. We are interested in the asymptotic behavior…

Probability · Mathematics 2024-04-16 Sherzod M. Mirakhmedov
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