Forward interval propagation through the Fourier discrete transform

12/17/2020
by   Marco De Angelis, et al.
0

In this paper an algorithm for the forward interval propagation on the amplitude of the discrete Fourier transform (DFT) is presented. The algorithm yields best-possible bounds on the amplitude of the DFT for real and complex valued sequences. We show that computing the exact bounds for the amplitude of the DFT can be achieved with an exhaustive examination of all possible corners of the interval-shaped domain. However, because the number of corners increase exponentially (in base 2) with the number of intervals, such method is infeasible for large interval signals. We provide an algorithm that does not need such an exhaustive search, and show that the best possible bounds for the amplitude can be obtained propagating complex pairs only from the convex hull. Because the convex hull is always tightly inscribed in the respective rigorous bounding box resulting from interval arithmetic, we conclude that the obtained bounds are guaranteed to yield the true bounds.

READ FULL TEXT
research
05/27/2022

Exact bounds on the amplitude and phase of the interval discrete Fourier transform in polynomial time

We elucidate why an interval algorithm that computes the exact bounds on...
research
01/13/2023

An artificially-damped Fourier method for dispersive evolution equations

Computing solutions to partial differential equations using the fast Fou...
research
09/11/2003

Using Propagation for Solving Complex Arithmetic Constraints

Solving a system of nonlinear inequalities is an important problem for w...
research
12/22/2017

Probabilistic Eigenvalue Shaping for Nonlinear Fourier Transform Transmission

We consider a nonlinear Fourier transform (NFT)-based transmission schem...
research
05/06/2022

An exact quantum order finding algorithm and its applications

We present an efficient exact quantum algorithm for order finding proble...
research
02/24/2020

Markov Logic Networks with Complex Weights: Expressivity, Liftability and Fourier Transforms

We study expressivity of Markov logic networks (MLNs). We introduce comp...
research
05/15/2014

CDF-Intervals: A Reliable Framework to Reason about Data with Uncertainty

This research introduces a new constraint domain for reasoning about dat...

Please sign up or login with your details

Forgot password? Click here to reset