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In this paper, using the tools from the lineability theory, we distinguish certain subsets of $p$-adic differentiable functions. Specifically, we show that the following sets of functions are large enough to contain an infinite dimensional…

Boolean functions with good cryptographic criteria when restricted to the set of vectors with constant Hamming weight play an important role in the recent FLIP stream cipher. In this paper, we propose a large class of weightwise perfectly…

Cryptography and Security · Computer Science 2017-09-12 Jian Liu , Sihem Mesnager

In this paper, we prove that sufficiently regular solutions of any quasilinear PDE can be approximated by solutions of systems of N distinguishable particles, to within 1/ ln(N ). This intruiguing result is related to recent developments in…

Analysis of PDEs · Mathematics 2025-01-22 Thierry Paul , Emmanuel Trélat

We contribute to the exceptional APN conjecture by showing that no polynomial of degree m = 2 r (2 {\ell} + 1) where gcd(r, {\ell}) 2, r 2, {\ell} 1 with a nonzero second leading coefficient can be APN over infinitely many extensions of the…

Number Theory · Mathematics 2022-07-29 Yves Aubry , Fabien Herbaut , Ali Issa

In this article we introduce a class of discontinuous almost automorphic functions which appears naturally in the study of almost automorphic solutions of differential equations with piecewise constant argument. Their fundamental properties…

Classical Analysis and ODEs · Mathematics 2013-06-06 A. Chavez , S. Castillo , M. Pinto

Differential cryptanalysis famously uses statistical biases in the propagation of differences in a block cipher to attack the cipher. In this paper, we investigate the existence of more general statistical biases in the differences. To this…

Cryptography and Security · Computer Science 2022-08-09 Daniele Bartoli , Lukas Kölsch , Giacomo Micheli

We consider a class of "box-like" statistically self-affine functions, and compute the almost-sure box-counting dimension of their graphs. Furthermore, we consider the differentiability of our functions, and prove that, depending on an…

Classical Analysis and ODEs · Mathematics 2023-06-21 Pieter Allaart , Taylor Jones

In this paper we look at normed spaces of differentiable functions on compact plane sets, including the spaces of infinitely differentiable functions originally considered by Dales and Davie. For many compact plane sets the classical…

Functional Analysis · Mathematics 2007-05-23 W. J. Bland , J. F. Feinstein

This paper investigates the universal approximation capabilities of Hamiltonian Deep Neural Networks (HDNNs) that arise from the discretization of Hamiltonian Neural Ordinary Differential Equations. Recently, it has been shown that HDNNs…

Machine Learning · Computer Science 2023-05-31 Muhammad Zakwan , Massimiliano d'Angelo , Giancarlo Ferrari-Trecate

The article is devoted to approximate, global and along curves differentiability of functions over non-archimedean infinite fields with non-trivial valuations. Fields with zero and non-zero characteristics are considered. Spaces of…

Classical Analysis and ODEs · Mathematics 2010-03-16 S. V. Ludkovsky

Almost Perfect Nonlinear (APN) functions are very useful in cryptography, when they are used as S-Boxes, because of their good resistance to differential cryptanalysis. An APN function $f:\mathbb{F}_{2^n}\rightarrow\mathbb{F}_{2^n}$ is…

Number Theory · Mathematics 2016-02-09 Moises Delgado , Heeralal Janwa

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

In the present article, we introduce and study the behaviour of the new family of exponential type neural network operators activated by the sigmoidal functions. We establish the point-wise and uniform approximation theorems for these NN…

Numerical Analysis · Mathematics 2019-11-14 S. Bajpeyi , A. Sathish Kumar

An almost perfect nonlinear (APN) function (necessarily a polynomial function) on a finite field $\mathbb{F}$ is called exceptional APN, if it is also APN on infinitely many extensions of $\mathbb{F}$. In this article we consider the most…

Information Theory · Computer Science 2012-07-25 Moises Delgado , Heeralal Janwa

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 1969, Delange has proved a general criterion for uniform distribution of additive functions. In this paper, we study the uniform distribution of a special class of polynomially-defined additive functions where the moduli is allowed to…

Number Theory · Mathematics 2024-01-10 Agbolade Patrick Akande

Given an observation of the uniform empirical process $\alp_n$, its functional increments $\alp_n(u+a_n\cdot)-\alp_n(u)$ can be viewed as a single random process, when $u$ is distributed under the Lebesgue measure. We investigate the almost…

Statistics Theory · Mathematics 2012-01-27 Davit Varron

Interpolation and approximation of functionals with conditionally positive definite kernels is considered on sets of centers that are not determining for polynomials. It is shown that polynomial consistency is sufficient in order to define…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

We show that neural networks with absolute value activation function and with the path norm, the depth, the width and the network weights having logarithmic dependence on $1/\varepsilon$ can $\varepsilon$-approximate functions that are…

Machine Learning · Statistics 2022-11-18 Aleksandr Beknazaryan

Functions with low differential uniformity can be used in a block cipher as S-boxes since they have good resistance to differential attacks. In this paper we consider piecewise constructions for permutations with low differential…

Information Theory · Computer Science 2020-09-22 Marco Calderini