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It is well-known that the controllability of finite-dimensional nonlinear systems can be established by showing the controllability of the linearized system. However, this classical result does not generalize to infinite-dimensional…

Optimization and Control · Mathematics 2021-07-29 Bernd Kolar , Markus Schöberl

The paper gives an overview of recent advances in structural equation modeling. A structural equation model is a multivariate statistical model that is determined by a mixed graph, also known as a path diagram. Our focus is on the…

Statistics Theory · Mathematics 2016-12-20 Mathias Drton

The well-known Asplund theorem states that the inverse of a (possibly one-sided) band matrix $A$ is a Green matrix. In accordance with quasiseparable theory, such a matrix admits a quasiseparable representation in its rank-structured part.…

Numerical Analysis · Mathematics 2025-11-05 Paola Boito , Yuli Eidelman

High dimensional covariance estimation and graphical models is a contemporary topic in statistics and machine learning having widespread applications. An important line of research in this regard is to shrink the extreme spectrum of the…

Methodology · Statistics 2016-06-28 Sang-Yun Oh , Bala Rajaratnam , Joong-Ho Won

Some mutually quasi-unbiased weighing matrices are constructed from binary codes satisfying certain conditions. Motivated by this, in this note, we study binary codes satisfying the conditions. The weight distributions of binary codes…

Combinatorics · Mathematics 2016-08-19 Masaaki Harada , Sho Suda

In this work we study the condition number of the least square matrix corresponding to scale free networks. We compute a theoretical lower bound of the condition number which proves that they are ill conditioned. Also, we analyze several…

Disordered Systems and Neural Networks · Physics 2016-08-16 Gabriel Acosta , Matías Graña , Juan Pablo Pinasco

Probabilistic circuits (PCs) are a prominent representation of probability distributions with tractable inference. While parameter learning in PCs is rigorously studied, structure learning is often more based on heuristics than on…

Machine Learning · Computer Science 2023-02-24 Yang Yang , Gennaro Gala , Robert Peharz

We consider concurrent systems consisting of a finite but unknown number of components, that are replicated instances of a given set of finite state automata. The components communicate by executing interactions which are simultaneous…

Formal Languages and Automata Theory · Computer Science 2019-02-08 Marius Bozga , Radu Iosif , Joseph Sifakis

We perform a smoothed analysis of the componentwise condition numbers for determinant computation, matrix inversion, and linear equations solving for sparse n times n matrices. The bounds we obtain for the ex- pectations of the logarithm of…

Numerical Analysis · Mathematics 2013-02-26 Dennis Cheung , Felipe Cucker

In this paper, we consider the explicit expressions of the normwise condition number for the scaled total least squares problem. Some techniques are introduced to simplify the expression of the condition number, and some new results are…

Numerical Analysis · Mathematics 2019-07-08 Shaoxin Wang , Hanyu Li , Hu Yang

We consider the problem of estimating a high-dimensional covariance matrix from a small number of observations when covariates on pairs of variables are available and the variables can have spatial structure. This is motivated by the…

We present sufficient conditions under which a given linear nonautonomous system and its nonlinear perturbation are topologically conjugated. Our conditions are of a very general form and provided that the nonlinear perturbations are…

Classical Analysis and ODEs · Mathematics 2022-10-12 Lucas Backes , Davor Dragičević

A large family of linear codes with flexible parameters from almost bent functions and perfect nonlinear functions are constructed and their parameters are determined. Some constructed linear codes and their related codes are optimal in the…

Information Theory · Computer Science 2019-03-20 Weiqiong Wang , Yan Wang

We show that the mass matrix derived from finite elements can be effectively used as a preconditioner for iteratively solving the linear system arising from finite-difference discretization of the Poisson equation, using the conjugate…

Numerical Analysis · Mathematics 2021-11-08 Chen Greif , Yunhui He

We investigate the relation between multilinear mappings and multipartite states. We show that the isomorphism between multilinear mapping and tensor product completely characterizes decomposable multipartite states in a mathematically…

Quantum Physics · Physics 2009-01-02 Hoshang Heydari

We consider a symmetric matrix, the entries of which depend linearly on some parameters. The domains of the parameters are compact real intervals. We investigate the problem of checking whether for each (or some) setting of the parameters,…

Numerical Analysis · Computer Science 2019-05-28 Milan Hladík

A matrix (and any associated linear system) will be referred to as structured if it has a small displacement rank. It is known that the inverse of a structured matrix is structured, which allows fast inversion (or solution), and reduced…

Numerical Analysis · Mathematics 2008-12-18 Pierre Comon

We conduct a condition number analysis of a Hybrid High-Order (HHO) scheme for the Poisson problem. We find the condition number of the statically condensed system to be independent of the number of faces in each element, or the relative…

Numerical Analysis · Mathematics 2022-07-11 Santiago Badia , Jerome Droniou , Liam Yemm

This paper proposes a theoretical framework for analyzing Modified Incomplete LU (MILU) preconditioners. Considering a generalized MILU preconditioner on a weighted undirected graph with self-loops, we extend its applicability beyond…

Numerical Analysis · Mathematics 2025-01-03 Geonho Hwang , Yesom Park , Yueun Lee , Jooyoung Hahn , Myungjoo Kang

We numerically analyze the statistical properties of complex system with conditions subjecting the matrix elements to a set of specific constraints besides symmetry, resulting in various structures in their matrix representation. Our…

Disordered Systems and Neural Networks · Physics 2019-02-20 Triparna Mondal , Pragya Shukla
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