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There exists a huge number of numerical methods that iteratively construct approximations to the solution $y(x)$ of an ordinary differential equation (ODE) $y'(x)=f(x,y)$ starting from an initial value $y_0=y(x_0)$ and using a finite…

Numerical Analysis · Mathematics 2013-07-15 Yaroslav D. Sergeyev

We propose a new order, the small polynomial path order (sPOP* for short). The order sPOP* provides a characterisation of the class of polynomial time computable function via term rewrite systems. Any polynomial time computable function…

Computational Complexity · Computer Science 2012-01-17 Martin Avanzini , Naohi Eguchi , Georg Moser

Various problems on integers lead to the class of congruence preserving functions on rings, i.e. functions verifying $a-b$ divides $f(a)-f(b)$ for all $a,b$. We characterized these classes of functions in terms of sums of rational…

Number Theory · Mathematics 2015-06-02 Patrick Cégielski , Serge Grigorieff , Irène Guessarian

We show a general method allowing the solution calculation, in the form of a power series, for a very large class of nonlinear Ordinary Differential Equations (ODEs), namely the real analytic $\sigma\pi$-ODEs (and, more in general, the real…

Dynamical Systems · Mathematics 2019-03-15 Francesco Carravetta

We study the theory of ordinary differential equations over a commutative finite dimensional real associative unital algebra $\mathcal{A}$. We call such problems $\mathcal{A}$-ODEs. If a function is real differentiable and its differential…

Rings and Algebras · Mathematics 2017-08-15 Nathan BeDell , James S. Cook

In this paper we develop general techniques for classes of computable real numbers generated by subsets of total computable (recursive functions) with special restrictions on basic operations in order to investigate the following problems:…

Logic · Mathematics 2020-11-18 M. V. Korovina , O. V. Kudinov

Ordinary differential equations (ODEs) are a conventional way to describe the observed dynamics of physical systems. Scientists typically hypothesize about dynamical behavior, propose a mathematical model, and compare its predictions to…

Machine Learning · Computer Science 2025-11-20 Nils Wildt , Daniel M. Tartakovsky , Sergey Oladyshkin , Wolfgang Nowak

Algebraic characterizations of the computational aspects of functions defined over the real numbers provide very effective tool to understand what computability and complexity over the reals, and generally over continuous spaces, mean. This…

Logic in Computer Science · Computer Science 2016-09-27 Olivier Bournez , Walid Gomaa , Emmanuel Hainry

In this paper some classes of local polynomial functions on abelian groups are characterized by the properties of their variety. For this characterization we introduce a numerical quantity depending on the variety of the local polynomial…

Functional Analysis · Mathematics 2014-04-02 J. M. Almira , L. Székelyhidi

Toda proved in 1989 that the (discrete) polynomial time hierarchy, $\mathbf{PH}$, is contained in the class $\mathbf{P}^{#\mathbf{P}}$, namely the class of languages that can be decided by a Turing machine in polynomial time given access to…

Computational Complexity · Computer Science 2011-02-02 Saugata Basu , Thierry Zell

We introduce partial differential encodings of Boolean functions as a way of measuring the complexity of Boolean functions. These encodings enable us to derive from group actions non-trivial bounds on the Chow-Rank of polynomials used to…

Computational Complexity · Computer Science 2022-12-02 Edinah K. Gnang , Rongyu Xu

We introduce a basis of rational polynomial-like functions $P_0,\ldots,P_{n-1}$ for the free module of functions $Z/nZ\to Z/mZ$. We then characterize the subfamily of congruence preserving functions as the set of linear combinations of the…

Number Theory · Mathematics 2015-06-02 Patrick Cegielski , Serge Grigorieff , Irene Guessarian

The idea of neural Ordinary Differential Equations (ODE) is to approximate the derivative of a function (data model) instead of the function itself. In residual networks, instead of having a discrete sequence of hidden layers, the…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Seyedalireza Khoshsirat , Chandra Kambhamettu

The synthesis of classical Computational Complexity Theory with Recursive Analysis provides a quantitative foundation to reliable numerics. Here the operators of maximization, integration, and solving ordinary differential equations are…

Numerical Analysis · Computer Science 2012-11-22 Akitoshi Kawamura , Norbert Th. Müller , Carsten Rösnick , Martin Ziegler

To better understand and improve the behavior of neural networks, a recent line of works bridged the connection between ordinary differential equations (ODEs) and deep neural networks (DNNs). The connections are made in two folds: (1) View…

Machine Learning · Computer Science 2019-11-05 Xinshi Chen

Algorithms for the symbolic computation of polynomial conservation laws, generalized symmetries, and recursion operators for systems of nonlinear differential-difference equations (DDEs) are presented. The algorithms can be used to test the…

Mathematical Physics · Physics 2011-04-26 Ünal Göktaş , Willy Hereman

Algorithms for the computation of the real zeros of hypergeometric functions which are solutions of second order ODEs are described. The algorithms are based on global fixed point iterations which apply to families of functions satisfying…

Numerical Analysis · Mathematics 2025-10-20 Amparo Gil , Wolfram Koepf , Javier Segura

In this paper we consider a fragment of the first-order theory of the real numbers that includes systems of equations of continuous functions in bounded domains, and for which all functions are computable in the sense that it is possible to…

Computational Complexity · Computer Science 2016-08-15 Peter Franek , Stefan Ratschan , Piotr Zgliczynski

A method of representation of a solution as segments of the series in powers of the step of the independent variable is expanded for solving complex systems of ordinary differential equations (ODE): the Lorenz system and other systems. A…

Numerical Analysis · Computer Science 2014-05-26 Vladimir Aristov , Andrey Stroganov

Ordinary differential equations (ODEs), via their induced flow maps, provide a powerful framework to parameterize invertible transformations for the purpose of representing complex probability distributions. While such models have achieved…

Statistics Theory · Mathematics 2023-09-06 Youssef Marzouk , Zhi Ren , Sven Wang , Jakob Zech
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