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We study a natural complexity measure of Boolean functions known as the rational degree. Denoted $\textrm{rdeg}(f)$, it is the minimal degree of a rational function that is equal to $f$ on the Boolean hypercube. For total functions $f$, it…

Computational Complexity · Computer Science 2025-04-16 Vishnu Iyer , Siddhartha Jain , Robin Kothari , Matt Kovacs-Deak , Vinayak M. Kumar , Luke Schaeffer , Daochen Wang , Michael Whitmeyer

Recursive analysis was introduced by A. Turing [1936], A. Grzegorczyk [1955], and D. Lacombe [1955]. It is based on a discrete mechanical framework that can be used to model computation over the real numbers. In this context the…

Computational Complexity · Computer Science 2009-11-13 Walid Gomaa

We present a method for constructing global analytical expressions that approximate a function over its entire range. These approximations not only mirror the original function as accurately as desired, but are purposefully created to…

High Energy Physics - Phenomenology · Physics 2024-07-09 Aviv Orly

Neural networks are versatile tools for computation, having the ability to approximate a broad range of functions. An important problem in the theory of deep neural networks is expressivity; that is, we want to understand the functions that…

Machine Learning · Computer Science 2021-08-16 Khashayar Filom , Konrad Paul Kording , Roozbeh Farhoodi

Fourier series multiscale method, a concise and efficient analytical approach for multiscale computation, will be developed out of this series of papers. The second paper is concerned with simultaneous approximation to functions and their…

Numerical Analysis · Mathematics 2022-08-09 Weiming Sun , Zimao Zhang

Noncommutative rational functions, i.e., elements of the universal skew field of fractions of a free algebra, can be defined through evaluations of noncommutative rational expressions on tuples of matrices. This interpretation extends their…

Rings and Algebras · Mathematics 2018-04-24 Jurij Volčič

Transcendental functions, such as exponentials and logarithms, appear in a broad array of computational domains: from simulations in curvilinear coordinates, to interpolation, to machine learning. Unfortunately they are typically expensive…

Computational Physics · Physics 2022-06-22 Jonah M. Miller , Joshua C. Dolence , Daniel Holladay

The suitable basis functions for approximating periodic function are periodic, trigonometric functions. When the function is not periodic, a viable alternative is to consider polynomials as basis functions. In this paper we will point out…

Numerical Analysis · Mathematics 2013-01-01 Hillel Tal-Ezer

Provided a special function of one variable and some of its derivatives can be accurately computed over a finite range, a method is presented to build a series of polynomial approximations of the function with a defined relative error over…

Computational Physics · Physics 2007-05-23 C. Semay

We consider the problem of representing Boolean functions exactly by "sparse" linear combinations (over $\mathbb{R}$) of functions from some "simple" class ${\cal C}$. In particular, given ${\cal C}$ we are interested in finding…

Computational Complexity · Computer Science 2018-02-27 R. Ryan Williams

We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral…

Numerical Analysis · Mathematics 2012-07-17 Erwan Faou , Fabio Nobile , Christophe Vuillot

A selection of algorithms for the rational approximation of matrix-valued functions are discussed, including variants of the interpolatory AAA method, the RKFIT method based on approximate least squares fitting, vector fitting, and a method…

Numerical Analysis · Mathematics 2021-04-21 Ion Victor Gosea , Stefan Güttel

We describe an adaptive greedy algorithm for Thiele continued-fraction approximation of a function defined on a continuum domain in the complex plane. The algorithm iteratively selects interpolation nodes from an adaptively refined set of…

Numerical Analysis · Mathematics 2025-10-09 Tobin A. Driscoll , Yuxing Zhou

We present an extension of the AAA (adaptive Antoulas--Anderson) algorithm for periodic functions, called 'AAAtrig'. The algorithm uses the key steps of AAA approximation by (i) representing the approximant in (trigonometric) barycentric…

Numerical Analysis · Mathematics 2020-08-13 Peter J. Baddoo

In 2012 Chen and Singer introduced the notion of discrete residues for rational functions as a complete obstruction to rational summability. More explicitly, for a given rational function f(x), there exists a rational function g(x) such…

Symbolic Computation · Computer Science 2025-03-21 Carlos E. Arreche , Hari P. Sitaula

Consider a subfield of the field of rational functions in several indeterminates. We present an algorithm that, given a set of generators of such a subfield, finds a simple generating set. We provide an implementation of the algorithm and…

Symbolic Computation · Computer Science 2026-03-06 Alexander Demin , Gleb Pogudin

Let f be holomorphically continuable over the complex plane except for finitely many branch points contained in the unit disk. We prove that best rational approximants to f of degree n, in the L^2-sense on the unit circle, have poles that…

Classical Analysis and ODEs · Mathematics 2011-11-08 Laurent Baratchart , Herbert Stahl , Maxim Yattselev

We consider simple rational functions $R_{mn}(x)=P_m(x)/Q_n(x)$, with $P_m$ and $Q_n$ polynomials of degree $m$ and $n$ respectively. We look for "nice" functions, which we define to be ones where as many as possible of the roots, poles,…

Number Theory · Mathematics 2013-12-09 Allan J. MacLeod

Function fitting/approximation plays a fundamental role in computer graphics and other engineering applications. While recent advances have explored neural networks to address this task, these methods often rely on architectures with many…

Graphics · Computer Science 2025-05-28 Biao Zhang , Peter Wonka

Fractional differential equations (FDEs) describe subdiffusion behavior of dynamical systems. Its non-local structure requires taking into account the whole evolution history during the time integration, which then possibly causes…

Numerical Analysis · Mathematics 2022-02-17 Ustim Khristenko , Barbara Wohlmuth