Affiliation:
1. Univ Rennes, CNRS, IRMAR–UMR 6625, F-35000 Rennes, France
Abstract
Abstract
In this paper, we investigate the local universality of the number of zeros of a random periodic signal of the form $S_n(t)=\sum _{k=1}^n a_k f(k t)$, where $f$ is a $2\pi -$periodic function satisfying weak regularity conditions and where the coefficients $a_k$ are i.i.d. random variables, which are centered with unit variance. In particular, our results hold for continuous piecewise linear functions. We prove that the number of zeros of $S_n(t)$ in a shrinking interval of size $1/n$ converges in law as $n$ goes to infinity to the number of zeros of a Gaussian process whose explicit covariance only depends on the function $f$ and not on the common law of the random coefficients $(a_k)$. As a byproduct, this entails that the point measure of the zeros of $S_n(t)$ converges in law to an explicit limit on the space of locally finite point measures on $\mathbb R$ endowed with the vague topology. The standard tools involving the regularity or even the analyticity of $f$ to establish such kind of universality results are here replaced by some high-dimensional Berry–Esseen bounds recently obtained in [ 7]. The latter allow us to prove functional Central Limit Theorems in $C^1$ or Lipschitz topology in situations where usual criteria cannot be applied due to the lack of regularity.
Funder
Agence Nationale de la Recherche
Publisher
Oxford University Press (OUP)
Reference17 articles.
1. Institute of Mathematical Statistics Lecture Notes—Monograph Series;Adler,1990
2. Universality of the nodal length of bivariate random trigonometric polynomials;Angst;Trans. Amer. Math. Soc.,2018
3. Level Sets and Extrema of Random Processes and Fields
4. Wiley Series in Probability and Statistics: Probability and Statistics;Billingsley,1999
5. Random Eigenfunctions on flat Tori: universality for the number of intersections;Chang;Int. Math. Res. Notices,2018
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Limit theorems for random Dirichlet series;Stochastic Processes and their Applications;2023-11