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In this paper we study the asymptotic theory for spectral analysis of stationary random fields, including linear and nonlinear fields. Asymptotic properties of Fourier coefficients and periodograms, including limiting distributions of…

Statistics Theory · Mathematics 2021-10-28 Wai Leong Ng , Chun Yip Yau

We prove a necessary condition for some polynomials of degree 4e (e an odd number) to be APN over F q n for large n, and we investigate the polynomials f of degree 12.

Number Theory · Mathematics 2016-02-03 François Rodier

We present new algorithms to compute fundamental properties of a Boolean function given in truth-table form. Specifically, we give an O(N^2.322 log N) algorithm for block sensitivity, an O(N^1.585 log N) algorithm for `tree decomposition,'…

Computational Complexity · Computer Science 2007-05-23 Scott Aaronson

We study the trapezoidal rule for periodic functions on uniform grids and show that the quadrature error exhibits a rich deterministic structure, beyond traditional asymptotic or statistical interpretations. Focusing on the prototype…

General Mathematics · Mathematics 2025-05-06 William Cook

The characterization of a binary function by partial frequency information is considered. We show that it is possible to reconstruct binary signals from incomplete frequency measurements via the solution of a simple linear optimization…

Information Theory · Computer Science 2012-04-19 Yu Mao

In this paper, by the Hasse-Weil bound, we determine the necessary and sufficient condition on coefficients $a_1,a_2,a_3\in\mathbb{F}_{2^n}$ with $n=2m$ such that $f(x) = {x}^{3\cdot2^m} + a_1x^{2^{m+1}+1} + a_2 x^{2^m+2} + a_3x^3$ is an…

Information Theory · Computer Science 2020-07-09 Kangquan Li , Chunlei Li , Tor Helleseth , Longjiang Qu

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

In many applications data are measured or defined on a spherical manifold; spherical harmonic transforms are then required to access the frequency content of the data. We derive algorithms to perform forward and inverse spin spherical…

Astrophysics · Physics 2011-10-28 J. D. McEwen

We prove characterizations of Appell polynomials by means of symmetric property. For these polynomials, we establish a simple linear expression in terms of Bernoulli and Euler polynomials. As applications, we give interesting examples. In…

Number Theory · Mathematics 2021-03-01 Abdelmejid Bayad , Takao Komatsu

Invariance under symmetry is an important problem in machine learning. Our paper looks specifically at equivariant neural networks where transformations of inputs yield homomorphic transformations of outputs. Here, steerable CNNs have…

Machine Learning · Computer Science 2021-09-15 Daniel Franzen , Michael Wand

We consider the multiplicative complexity of Boolean functions with multiple bits of output, studying how large a multiplicative complexity is necessary and sufficient to provide a desired nonlinearity. For so-called $\Sigma\Pi\Sigma$…

Computational Complexity · Computer Science 2018-02-23 Magnus Gausdal Find , Joan Boyar

Recent measurement of the structure function $F_2^\nu$ in neutrino deep inelastic scattering allows us to compare structure function measured in neutrino and charged lepton scattering for the first time with reasonable precision. The…

High Energy Physics - Phenomenology · Physics 2007-05-23 C. Boros

In this paper, we consider the problem of reconstructing piecewise smooth functions to high accuracy from nonuniform samples of their Fourier transform. We use the framework of nonuniform generalized sampling (NUGS) to do this, and to…

Numerical Analysis · Mathematics 2014-10-02 Ben Adcock , Milana Gataric , Anders C. Hansen

This paper explores methods for verifying the properties of Binary Neural Networks (BNNs), focusing on robustness against adversarial attacks. Despite their lower computational and memory needs, BNNs, like their full-precision counterparts,…

Machine Learning · Computer Science 2025-04-16 Jianting Yang , Srećko Ðurašinović , Jean-Bernard Lasserre , Victor Magron , Jun Zhao

Physics-Informed Neural Networks (PINNs) have emerged as a promising approach for solving Partial Differential Equations (PDEs). However, they face challenges related to spectral bias (the tendency to learn low-frequency components while…

Neural and Evolutionary Computing · Computer Science 2025-06-16 Afrah Farea , Mustafa Serdar Celebi

Linear codes with few weights have many applications in secret sharing schemes, authentication codes, communication and strongly regular graphs. In this paper, we consider linear codes with three weights in arbitrary characteristic. To do…

Information Theory · Computer Science 2017-03-27 Sihem Mesnager , Ferruh Özbudak , Ahmet Sınak

Linear codes have diverse applications in secret sharing schemes, secure two-party computation, association schemes, strongly regular graphs, authentication codes and communication. There are a large number of linear codes with few weights…

Information Theory · Computer Science 2020-05-12 Ahmet Sınak

By means of partial fraction method, we investigate the decomposition of rational functions. Several striking identities on harmonic numbers and generalized Apery numbers will be established, including the binomial-harmonic number identity…

Combinatorics · Mathematics 2007-05-23 Wenchang Chu

In the literature, there are many APN-like functions that generalize the APN properties or are similar to APN functions, e.g. locally-APN functions, 0-APN functions or those with boomerang uniformity 2. In this paper, we study the problem…

Information Theory · Computer Science 2022-09-28 Longjiang Qu , Kangquan Li

Recently, several studies have shown that when $q\equiv3\pmod{4}$, for certain choices of $r$, the function $F_r(x)=x^r+x^{r+\frac{q-1}{2}}$ defined over $\Fq$ is locally-APN and has boomerang uniformity at most~$2$. In this paper, we…

Information Theory · Computer Science 2026-04-28 Namhun Koo , Soonhak Kwon , Minwoo Ko , Byunguk Kim