7 papers · 1 filter
Discretization, sampling, and the Fourier ratio
A. Iosevich, E. Palsson, A. Yavicoli
We derive fundamental sampling bounds for smooth signals in continuous settings without sparsity assumptions. By introducing the Fourier ratio as a measure of spectral compressibil…
The Fourier Ratio: A Unifying Measure of Complexity for Recovery, Localization, and Learning
Will Burstein, Alex Iosevich, Hari Sarang Nathan
We introduce a generalized Fourier ratio, the \(\ell^1/\ell^2\) norm ratio of coefficients in an \emph{arbitrary} orthonormal system, as a single, basis-invariant measure of \emph{…
The Fourier Ratio and complexity of signals
K. Aldaleh, W. Burstein, G. Garza +12
We study the Fourier ratio of a signal , \[ \mathrm{FR}(f)\ :=\ \sqrt{N}\,\frac{\|\widehat f\|_{L^1(μ)}}{\|\widehat f\|_{L^2(μ)}} \ =\ \frac{\|\widehat f…
Orlicz spaces and the uncertainty principle
A. Iosevich, I. Li, Z. Li +1
Let be a finite signal. The classical uncertainty principle tells us that the product of the support of and the support of , the Fourier transform of , must sat…
Fourier minimization and imputation of time series
Will Burstein, Alex Iosevich, Azita Mayeli +1
One of the most common procedures in modern data analytics is filling in missing values in times series. For a variety of reasons, the data provided by clients to obtain a forecast…
Uncertainty Principle, annihilating pairs and Fourier restriction
Philippe Jaming, Alexander Iosevich, Azita Mayeli
Let be a locally compact abelian group, and let denote its dual group, equipped with a Haar measure. A variant of the uncertainty principle states that for any $S…