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We consider the problem of parameter estimation by the observations of deterministic signal in white gaussian noise. It is supposed that the signal has a singularity of cusp-type. The properties of the maximum likelihood and bayesian…

Statistics Theory · Mathematics 2015-09-10 Oleg Chernoyarov , Serguei Dachian , Yury Kutoyants

Sometimes, it is possible to represent a complicated polytope as a projection of a much simpler polytope. To quantify this phenomenon, the extension complexity of a polytope $P$ is defined to be the minimum number of facets of a (possibly…

Combinatorics · Mathematics 2022-03-24 Matthew Kwan , Lisa Sauermann , Yufei Zhao

Short and transparent proofs of central limit theorems for intrinsic volumes of random polytopes in smooth convex bodies are presented. They combine different tools such as estimates for floating bodies with Stein's method from probability…

Metric Geometry · Mathematics 2017-11-06 Christoph Thaele , Nicola Turchi , Florian Wespi

The convex hull of N independent random points chosen on the boundary of a simple polytope in R^n is investigated. Asymptotic formulas for the expected number of vertices and facets, and for the expectation of the volume difference are…

Probability · Mathematics 2022-01-11 M. Reitzner , C. Schuett , E. M. Werner

We study the set of no-signalling empirical models on a measurement scenario, and show that the combinatorial structure of the no-signalling polytope is completely determined by the possibilistic information given by the support of the…

Quantum Physics · Physics 2018-07-03 Samson Abramsky , Rui Soares Barbosa , Kohei Kishida , Raymond Lal , Shane Mansfield

We consider the problem of recovering linear image $Bx$ of a signal $x$ known to belong to a given convex compact set $X$ from indirect observation $\omega=Ax+\sigma\xi$ of $x$ corrupted by Gaussian noise $\xi$. It is shown that under some…

Statistics Theory · Mathematics 2019-10-22 Anatoli Juditsky , Arkadi Nemirovski

Analysis of non-asymptotic estimation error and structured statistical recovery based on norm regularized regression, such as Lasso, needs to consider four aspects: the norm, the loss function, the design matrix, and the noise model. This…

Machine Learning · Statistics 2015-12-01 Arindam Banerjee , Sheng Chen , Farideh Fazayeli , Vidyashankar Sivakumar

We construct several sequences of asymptotically optimal definite quadrature formulae of fourth order and evaluate their error constants. Besides the asymptotical optimality, an advantage of our quadrature formulae is the explicit form of…

Numerical Analysis · Mathematics 2016-05-10 Ana Avdzhieva , Geno Nikolov

We study one-shot detection under isotropic multivariate Cauchy noise using finite constellations, with emphasis on the geometric mechanisms governing symbol-level reliability. Under isotropic Cauchy noise, the maximum-likelihood rule…

Information Theory · Computer Science 2026-04-28 Yen-Chi Lee

We consider a model applicable in many communication systems where the sum of n stochastic sinusoidal signals of the same frequency, but with random amplitudes as well as phase angles is present. The exact probability distribution of the…

Information Theory · Computer Science 2019-11-13 Y. Maghsoodi , A. Al-Dweik

Paper [1] derived the probability density function (PDF) of a sum of products of two correlated complex Gaussian zero-mean random variables (RVs) that has been applied to calculate the error probabilities of a \emph{M}-ary phase shift…

Signal Processing · Electrical Eng. & Systems 2019-10-09 Trung-Hien Nguyen , Jerome Louveaux , Philippe De Doncker , Francois Horlin

We introduce and discuss the concept of Gaussian probability density function (pdf) for the n-dimensional hyperbolic space which has been proposed as an environment for coding and decoding signals. An upper bound for the error probability…

Information Theory · Computer Science 2011-01-21 Edson Agustini , Sueli I. R. Costa

An expression for the joint probability distribution of the principal curvatures at an arbitrary point in the ensemble of isosurfaces defined on isotropic Gaussian random fields on Rn is derived. The result is obtained by deriving symmetry…

Mathematical Physics · Physics 2007-05-23 Paulo R. S. Mendonca , Rahul Bhotika , James V. Miller

This paper describes how a priori information about the signal parameters can influence the accuracy of estimating the number of these signals. This study considers sinusoidal signals and it is supposed that the parameters (amplitudes,…

Signal Processing · Electrical Eng. & Systems 2020-09-03 Aleksandr Kharin , Oleg V. Chernoyarov

This document derives several expected values related to the parameterized mean model with Gaussian noise and their simplified forms.

Probability · Mathematics 2012-09-11 Umut Orguner

We prove that for $n>3$ each generic simple polytope in $\mathbb{R}^n$ contains a point with at least $2n+4$ emanating normals to the boundary. This result is a piecewise-linear counterpart of a long-standing problem about normals to smooth…

Metric Geometry · Mathematics 2026-01-13 Ivan Nasonov , Gaiane Panina

There are (at least) two reasons to study random polytopes. The first is to understand the combinatorics and geometry of random polytopes especially as compared to other classes of polytopes, and the second is to analyze average-case…

Probability · Mathematics 2019-05-02 Andrew Newman

Consider a real-valued function that can only be observed with stochastic noise at a finite set of design points within a Euclidean space. We wish to determine whether there exists a convex function that goes through the true function…

Other Statistics · Statistics 2018-07-30 Nanjing Jian , Shane G. Henderson

Signal processing in non-Gaussian noise environment is addressed in this paper. For many real-life situations, the additive noise process present in the system is found to be dominantly non-Gaussian. The problem of detection and estimation…

Statistics Theory · Mathematics 2014-01-23 Jugalkishore K. Banoth , Pradip Sircar

A uniform asymptotic theory of the free-space paraxial propagation of coherent flattened Gaussian beams is proposed in the limit of nonsmall Fresnel numbers. The pivotal role played by the error function in the mathematical description of…

Optics · Physics 2016-01-20 Riccardo Borghi