Generalized gaussian bounds for discrete convolution powers

12/17/2020
by   Jean-François Coulombel, et al.
0

We prove a uniform generalized gaussian bound for the powers of a discrete convolution operator in one space dimension. Our bound is derived under the assumption that the Fourier transform of the coefficients of the convolution operator is a trigonometric rational function, which generalizes previous results that were restricted to trigonometric polynomials. We also allow the modulus of the Fourier transform to attain its maximum at finitely many points over a period.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/17/2019

Discrete and Fast Fourier Transform Made Clear

Fast Fourier transform was included in the Top 10 Algorithms of 20th Cen...
research
11/05/2021

The Fourier Transform of Restrictions of Functions on the Slice

This paper considers the Fourier transform over the slice of the Boolean...
research
01/15/2020

Mermin Polynomials for Entanglement Evaluation in Grover's algorithm and Quantum Fourier Transform

The entanglement of a quantum system can be valuated using Mermin polyno...
research
02/21/2017

Convolution Aware Initialization

Initialization of parameters in deep neural networks has been shown to h...
research
10/11/2022

Deep Fourier Up-Sampling

Existing convolutional neural networks widely adopt spatial down-/up-sam...
research
10/29/2019

Derivation and Analysis of Fast Bilinear Algorithms for Convolution

The prevalence of convolution in applications within signal processing, ...
research
05/22/2023

A Multiple Parameter Linear Scale-Space for one dimensional Signal Classification

In this article we construct a maximal set of kernels for a multi-parame...

Please sign up or login with your details

Forgot password? Click here to reset