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The Lambert W function gives the solutions of a simple exponential polynomial. The generalized Lambert W function was defined by Mez\"{o} and Baricz, and has found applications in delay differential equations and physics. In this article we…

Classical Analysis and ODEs · Mathematics 2018-01-31 Paul Castle

We provide sharp empirical estimates of expectation, variance and normal approximation for a class of statistics whose variation in any argument does not change too much when another argument is modified. Examples of such weak interactions…

Machine Learning · Statistics 2018-03-13 Andreas Maurer , Massimiliano Pontil

A new approach is presented for the calculation of p_n and pi_n which uses the Lambert W function. An approximation is first found and using a calculation technique it makes it possible to have an estimate of these two quantities more…

Number Theory · Mathematics 2020-06-04 Simon Plouffe

This paper concerns a time-independent thermoelectric model with two different boundary conditions. The model is a nonlinear coupled system of the Maxwell equations and an elliptic equation. By analyzing carefully the nonlinear structure of…

Analysis of PDEs · Mathematics 2019-09-04 Xing-Bin Pan , Zhibing Zhang

To decide upon the arithmetic nature of some numbers may be a non-trivial problem. Some cases are well know, for example exp(1) and W(1), where W is the Lambert function, are transcendental numbers. The Tsallis q-exponential, e_q (z), and…

Number Theory · Mathematics 2020-04-16 J. L. E. da Silva , R. V. Ramos

This paper technically explores the secrecy rate $\Lambda$ and a maximisation problem over the concave version of the secrecy outage probability (SOP) as $\mathop{{\rm \mathbb{M}ax}}\limits_{\Delta } {\rm \; } \mathbb{P}\mathscr{r} \big(…

Information Theory · Computer Science 2022-06-15 Makan Zamanipour

This paper studies the outage probability and the throughput of amplify-and-forward relay networks with wireless information and energy transfer. We use some recent results on finite block-length codes to analyze the system performance in…

Information Theory · Computer Science 2016-11-21 Mahdi Haghifam , Behrooz Makki , Masoumeh Nasiri-Kenari , Tommy Svensson , Michele Zorzi

Statistical divergences are important tools in data analysis, information theory, and statistical physics, and there exist well known inequalities on their bounds. However, in many circumstances involving temporal evolution, one needs…

Data Analysis, Statistics and Probability · Physics 2025-03-25 Jan Karbowski

We study the Laplace operator on domains subject to Dirichlet or Neumann boundary conditions. We show that these operators admit a bounded $H^{\infty}$-functional calculus on weighted Sobolev spaces, where the weights are powers of the…

Analysis of PDEs · Mathematics 2026-02-26 Nick Lindemulder , Emiel Lorist , Floris Roodenburg , Mark Veraar

Employing the Lagrange inverting series, a solution of the transcendental equation $(x-a)(x-b)=le^{x}$, that can be considered a quadratic generalization of the equation defining Lambert $W$ function, has been found in terms of Bessel…

Classical Analysis and ODEs · Mathematics 2015-04-28 Giorgio Mugnaini

In this paper, we investigate an approach to circuit lower bounds via bounded width circuits. The approach consists of two steps: (i) We convert circuits to (deterministic or nondeterministic) bounded width circuits. (ii) We prove lower…

Computational Complexity · Computer Science 2023-05-02 Hiroki Morizumi

A system of 'telegrapher's' equations for a number of long lines joined into a network is studied. Explicit formulas for Fourier transforms of current and voltage are derived. These formulas are very suitable for computer application as…

Classical Physics · Physics 2009-02-24 Nikolai Dokuchaev

We generalise the martingale-coboundary representation of discrete time stochastic processes to the non-stationary case and to random variables in Orlicz spaces. Related limit theorems (CLT, invariance principle, log log law, probabilities…

Probability · Mathematics 2023-11-07 Dalibor Volny

Linear differential equations and recurrences reveal many properties about their solutions. Therefore, these equations are well-suited for representing solutions and computing with special functions. We identify a large class of existing…

Symbolic Computation · Computer Science 2026-01-14 Louis Gaillard

This article investigates stationary surfaces with boundaries, which arise as the critical points of functionals dependent on curvature. Precisely, a generalized "bending energy" functional $\mathcal{W}$ is considered which involves a…

Differential Geometry · Mathematics 2021-10-15 Anthony Gruber , Magdalena Toda , Hung Tran

Herein, we present a canonical form for a natural and necessary generalization of the Lambert W function, natural in that it requires minimal mathematical definitions for this generalization, and necessary in that it provides a means of…

Mathematical Physics · Physics 2007-05-23 Tony C. Scott , Robert B. Mann

This paper proposes a new family of lower and upper bounds on the minimum mean squared error (MMSE). The key idea is to minimize/maximize the MMSE subject to the constraint that the joint distribution of the input-output statistics lies in…

Information Theory · Computer Science 2020-06-09 Michael Fauß , Alex Dysto , H. Vincent Poor

We give new bounds on the reliability function of a typewriter channel with 5 inputs and crossover probability $1/2$. The lower bound is more of theoretical than practical importance; it improves very marginally the expurgated bound,…

Information Theory · Computer Science 2016-07-19 Marco Dalai , Yury Polyanskiy

We consider distributed parameter estimation using interactive protocols subject to local information constraints such as bandwidth limitations, local differential privacy, and restricted measurements. We provide a unified framework…

Data Structures and Algorithms · Computer Science 2022-11-17 Jayadev Acharya , Clément L. Canonne , Ziteng Sun , Himanshu Tyagi

Optimal transport (OT) measures distances between distributions in a way that depends on the geometry of the sample space. In light of recent advances in computational OT, OT distances are widely used as loss functions in machine learning.…

Methodology · Statistics 2021-06-22 Debarghya Mukherjee , Aritra Guha , Justin Solomon , Yuekai Sun , Mikhail Yurochkin
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