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A deep neural network (DNN) with piecewise linear activations can partition the input space into numerous small linear regions, where different linear functions are fitted. It is believed that the number of these regions represents the…

Machine Learning · Computer Science 2020-04-30 Xiao Zhang , Dongrui Wu

We explore the block nature of the matrix representation of multiplex networks, introducing a new formalism to deal with its spectral properties as a function of the inter-layer coupling parameter. This approach allows us to derive…

Physics and Society · Physics 2018-07-17 Guilherme Ferraz de Arruda , Emanuele Cozzo , Francisco A. Rodrigues , Yamir Moreno

This paper presents a definition for local linearizations of rational matrices and studies their properties. This definition allows us to introduce matrix pencils associated to a rational matrix that preserve its structure of zeros and…

Numerical Analysis · Mathematics 2019-07-26 Froilán M. Dopico , Silvia Marcaida , María C. Quintana , Paul Van Dooren

A simple iterative scheme is proposed for locating the parameter values for which a 2-parameter family of real symmetric matrices has a double eigenvalue. The convergence is proved to be quadratic. An extension of the scheme to complex…

Spectral Theory · Mathematics 2021-07-27 Gregory Berkolaiko , Advait Parulekar

We extend classical time-frequency limiting analysis, historically applied to one-dimensional finite signals, to the multidimensional discrete setting. This extension is relevant for images, videos, and other multidimensional signals, as it…

Classical Analysis and ODEs · Mathematics 2025-07-15 Luis Gomez , Jonathan Jaimangal , Azita Mayeli , Tasfia Proma

A multidimensional nonnegative matrix is called polystochastic if the sum of entries in each line is equal to $1$. The set of all polystochastic matrices of order $n$ and dimension $d$ is a convex polytope $\Omega_n^d$. In the present…

Combinatorics · Mathematics 2025-12-01 Vladimir N. Potapov , Anna A. Taranenko

By excluding some regions, in which each eigenvalue of a matrix is not contained, from the \alpha\beta-type eigenvalue inclusion region provided by Huang et al.(Electronic Journal of Linear Algebra, 15 (2006) 215-224), a new eigenvalue…

Spectral Theory · Mathematics 2017-06-08 Suhua Li , Qingbing Liu , Chaoqian Li

We consider the problem of writing real polynomials as determinants of symmetric linear matrix polynomials. This problem of algebraic geometry, whose roots go back to the nineteenth century, has recently received new attention from the…

Algebraic Geometry · Mathematics 2011-08-23 Tim Netzer , Daniel Plaumann , Andreas Thom

We propose two approaches, based on Riemannian optimization, for computing a stochastic approximation of the $p$th root of a stochastic matrix $A$. In the first approach, the approximation is found in the Riemannian manifold of positive…

Numerical Analysis · Mathematics 2024-09-16 Fabio Durastante , Beatrice Meini

We investigate the properties of uniform doubly stochastic random matrices, that is non-negative matrices conditioned to have their rows and columns sum to 1. The rescaled marginal distributions are shown to converge to exponential…

Probability · Mathematics 2010-11-01 Sourav Chatterjee , Persi Diaconis , Allan Sly

We give a closed formula for the number of partitions $\lambda$ of $n$ such that the corresponding irreducible representation $V_\lambda$ of $S_n$ has non-trivial determinant. We determine how many of these partitions are self-conjugate and…

Representation Theory · Mathematics 2017-03-22 Arvind Ayyer , Amritanshu Prasad , Steven Spallone

We obtain the strong asymptotics of polynomials $p_n(\lambda)$, $\lambda\in\mathbb{C}$, orthogonal with respect to measures in the complex plane of the form $$ e^{-N(|\lambda|^{2s}-t\lambda^s-\overline{t\lambda}^s)}dA(\lambda), $$ where $s$…

Mathematical Physics · Physics 2016-07-05 Ferenc Balogh , Tamara Grava , Dario Merzi

It has been observed that the statistical distribution of the eigenvalues of random matrices possesses universal properties, independent of the probability law of the stochastic matrix. In this article we find the correlation functions of…

Condensed Matter · Physics 2009-10-30 B. Eynard

A matrix is well separated if all its Gershgorin circles are away from the unit circle and they are separated from each other. In this article, the region of relative errors in the eigenvalues is obtained as a quadratic oval for non…

General Mathematics · Mathematics 2020-12-22 M Hariprasad

This paper presents a general and systematic discussion of various symbolic representations of iterated maps through subshifts. We give a unified model for all continuous maps on a metric space, by representing a map through a general…

Chaotic Dynamics · Physics 2007-05-23 Xin-Chu Fu , Weiping Lu , Peter Ashwin , Jinqiao Duan

We consider unitary random matrix ensembles Z_{n,s,t}^{-1}e^{-n tr V_{s,t}(M)}dM on the space of Hermitian n x n matrices M, where the confining potential V_{s,t} is such that the limiting mean density of eigenvalues (as n\to\infty and…

Mathematical Physics · Physics 2009-11-11 T. Claeys , M. Vanlessen

It was shown recently by the authors that, for any n, there is equality between the distributions of certain triplets of statistics on nxn alternating sign matrices (ASMs) and descending plane partitions (DPPs) with each part at most n. The…

Combinatorics · Mathematics 2012-10-16 Roger E. Behrend , Philippe Di Francesco , Paul Zinn-Justin

In this paper, we answer the various forms of nonnegative inverse eigenvalue problems with prescribed diagonal entries for order three: real or complex general matrices, symmetric stochastic matrices, and real or complex doubly stochastic…

Spectral Theory · Mathematics 2018-06-22 Jin Ok Hwang , Donggyun Kim

Peter Denton, Stephen Parke, Terence Tao and Xining Zhang [arxiv 2019] presented a basic and important identity in linear commutative algebra, so-called {\bf the eigenvector-eigenvalue identity} (formally named in [BAMS, 2021]), which is a…

Rings and Algebras · Mathematics 2022-07-11 Yuchao He , Mengda Wu , Yonghui Xia

The main purpose of this paper is to obtain an explicit expression of a family of matrix valued orthogonal polynomials {P_n}_n, with respect to a weight W, that are eigenfunctions of a second order differential operator D. The weight W and…

Representation Theory · Mathematics 2007-05-23 I. Pacharoni , P. Roman