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Related papers: Directional Heisenberg uncertainty product

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In this paper we introduce a notion of a directional uncertainty product for multivariate periodic functions. It measures a localization of a function along a particular direction. We study properties of the uncertainty product and give an…

Functional Analysis · Mathematics 2018-08-30 A. Krivoshein , E. Lebedeva , J. Prestin

We introduce a notion of localization for dyadic functions, i.e. functions defined on the Cantor group. Localization is characterized by functional $UC_d$ similar to the Heisenberg uncertainty constant used for real-line functions. We are…

Classical Analysis and ODEs · Mathematics 2013-12-10 Aleksander V. Krivoshein , Elena A. Lebedeva

A central problem in signal processing and communications is to design signals that are compact both in time and frequency. Heisenberg's uncertainty principle states that a given function cannot be arbitrarily compact both in time and…

Information Theory · Computer Science 2014-01-17 Reza Parhizkar , Yann Barbotin , Martin Vetterli

The uncertainty product of a function is a quantity that measures the trade-off between the space and the frequency localization of the function. Its boundedness from below is the content of various uncertainty principles. In the present…

Classical Analysis and ODEs · Mathematics 2018-06-22 Ilona Iglewska-Nowak

An inequality refining the lower bound for a periodic (Breitenberger) uncertainty constant is proved for a wide class of functions. A connection of uncertainty constants for periodic and non-periodic functions is extended to this class. A…

Classical Analysis and ODEs · Mathematics 2015-03-31 Elena A. Lebedeva

We identity the optimal non-infinitesimal direction of descent for a convex function. An algorithm is developed that can theoretically minimize a subset of (non-convex) functions.

Optimization and Control · Mathematics 2025-09-19 Andrew J. Young

Divergence functions are interesting discrepancy measures. Even though they are not true distances, we can use them to measure how separated two points are. Curiously enough, when they are applied to random variables, they lead to a notion…

Statistics Theory · Mathematics 2018-09-21 Henryk Gzyl

The directional subdifferential of the value function gives an estimate on how much the optimal value changes under a perturbation in a certain direction. In this paper we derive upper estimates for the directional limiting and singular…

Optimization and Control · Mathematics 2023-04-19 Kuang Bai , Jane J. Ye

By use of window functions, time-frequency analysis tools like Short Time Fourier Transform overcome a shortcoming of the Fourier Transform and enable us to study the time- frequency characteristics of signals which exhibit transient os-…

Information Theory · Computer Science 2013-07-25 Sangnam Nam

Mainstream statistical methodology is generally applicable to data observed in Euclidean space. There are, however, numerous contexts of considerable scientific interest in which the natural supports for the data under consideration are…

Methodology · Statistics 2020-09-23 Arthur Pewsey , Eduardo García-Portugués

This report investigates the main definitions and fundamental properties of the fractional two-sided quaternionic Dunkl transform in two dimensions. We present key results concerning its structure and emphasize its connections to classical…

Functional Analysis · Mathematics 2025-10-14 Mohamed Essenhajy

In this paper the uncertainty principle is found via characteristics of continuous and nowhere differentiable functions. We prove that any physical system that has a continuous and nowhere differentiable position function is subject to an…

General Physics · Physics 2021-07-13 Faycal Ben Adda , Helene Porchon

Heisenberg's uncertainty relation is commonly regarded as defining a level of unpredictability that is fundamentally incompatible with the deterministic laws embodied in classical field theories such as Einstein's general relativity. We…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Paul S. Wesson

In this work, we introduce a hierarchy of function classes defined on a fixed compact interval, along with tailored uncertainty operators. We establish key properties of the associated uncertainty product, showing that it is invariant under…

Functional Analysis · Mathematics 2025-09-09 Lorenzo de Leonardis , Alessandro Mazzoccoli , Pierluigi Vellucci

Directional data arise in many applications where observations are naturally represented as unit vectors or as observations on the surface of a unit hypersphere. In this context, statistical depth functions provide a center--outward…

Methodology · Statistics 2026-02-24 Giuseppe Gismondi , Rebecca Rivieccio , Giuseppe Pandolfo

A cyclic random motion at finite velocity with orthogonal directions is considered in the plane and in $\mathbb{R}^3$. We obtain in both cases the explicit conditional distributions of the position of the moving particle when the number of…

Probability · Mathematics 2020-01-01 E. Orsingher , R. Garra , A. I. Zeifman

This paper sheds new light on regularity of multifunctions through various characterizations of directional H\"older /Lipschitz metric regularity, which are based on the concepts of slope and coderivative. By using these characterizations,…

Optimization and Control · Mathematics 2015-08-11 Van Ngai Huynh , Huu Tron Nguyen , Michel Théra

We introduce classifiers based on directional quantiles. We derive theoretical results for selecting optimal quantile levels given a direction, and, conversely, an optimal direction given a quantile level. We also show that the…

Methodology · Statistics 2020-09-14 Alessio Farcomeni , Marco Geraci , Cinzia Viroli

We formulate quantum mechanics in spacetimes with real-order fractional geometry and more general factorizable measures. In spacetimes where coordinates and momenta span the whole real line, Heisenberg's principle is proven and the…

High Energy Physics - Theory · Physics 2012-10-18 Gianluca Calcagni , Giuseppe Nardelli , Marco Scalisi

A sharper uncertainty inequality which exhibits a lower bound larger than that in the classical N-dimensional Heisenberg's uncertainty principle is obtained, and extended from N-dimensional Fourier transform domain to two N-dimensional…

Mathematical Physics · Physics 2019-06-14 Zhichao Zhang
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