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Consider $n \times n$ matrix $A$ and a set $\Lambda$ consisting of $k \le n$ prescribed complex numbers. Lippert (2010) in a challenging article, studied geometrically the spectral norm distance from $A$ to the set $\Lambda$ and constructed…

Numerical Analysis · Mathematics 2015-02-19 Esmaeil Kokabifar , Ghasem Barid Loghmani , S. M. Karbassi

We propose a novel parallel numerical algorithm for calculating the smallest eigenvalues of highly ill-conditioned matrices. It is based on the {\it LDLT} decomposition and involves finding a $k \times k$ sub-matrix of the inverse of the…

Numerical Analysis · Mathematics 2018-10-04 Yang Chen , Jakub Sikorowski , Mengkun Zhu

Given a nonlinear matrix-valued function $F(\lambda)$ and approximate eigenpairs $(\lambda_i, v_i)$, we discuss how to determine the smallest perturbation $\delta F$ such that $[F + \delta F](\lambda_i) v_i = 0$; we call the distance…

Numerical Analysis · Mathematics 2025-02-27 Miryam Gnazzo , Leonardo Robol

This paper presents a parallel algorithm for finding the smallest eigenvalue of a particular form of ill-conditioned Hankel matrix, which requires the use of extremely high precision arithmetic. Surprisingly, we find that commonly-used…

Numerical Analysis · Mathematics 2009-02-06 Niall Emmart , Charles C. Weems , Yang Chen

We investigate the large $N$ behavior of the smallest eigenvalue, $\lambda_{N}$, of an $\left(N+1\right)\times \left(N+1\right)$ Hankel (or moments) matrix $\mathcal{H}_{N}$, generated by the weight…

Mathematical Physics · Physics 2018-04-02 Mengkun Zhu , Yang Chen , Niall Emmart , Charles Weems

We study the asymptotic behavior of the smallest eigenvalue, $\lambda_{N}$, of the Hankel (or moments) matrix denoted by $\mathcal{H}_{N}=\left(\mu_{m+n}\right)_{0\leq m,n\leq N}$, with respect to the weight $w(x)=x^{\alpha}{\rm…

Mathematical Physics · Physics 2019-05-22 Mengkun Zhu , Niall Emmart , Yang Chen , Charles Weems

Given an appropriate class of structured matrices S; we characterize matrices X and B for which there exists a matrix A \in S such that AX = B and determine all matrices in S mapping X to B. We also determine all matrices in S mapping X to…

Numerical Analysis · Mathematics 2013-09-11 Bibhas Adhikari , Rafikul Alam

Given a square complex matrix $A$, we tackle the problem of finding the nearest matrix with multiple eigenvalues or, equivalently when $A$ had distinct eigenvalues, the nearest defective matrix. To this goal, we extend the general framework…

Numerical Analysis · Mathematics 2026-05-14 Vanni Noferini , Lauri Nyman , Federico Poloni

We propose and study an algorithm for computing a nearest passive system to a given non-passive linear time-invariant system (with much freedom in the choice of the metric defining `nearest', which may be restricted to structured…

Numerical Analysis · Mathematics 2021-03-04 Antonio Fazzi , Nicola Guglielmi , Christian Lubich

We study the robust matrix completion problem for the low-rank Hankel matrix, which detects the sparse corruptions caused by extreme outliers while we try to recover the original Hankel matrix from the partial observation. In this paper, we…

Information Theory · Computer Science 2025-04-17 HanQin Cai , Jian-Feng Cai , Juntao You

Let H_N=(s_{n+m}),n,m\le N denote the Hankel matrix of moments of a positive measure with moments of any order. We study the large N behaviour of the smallest eigenvalue lambda_N of H_N. It is proved that lambda_N has exponential decay to…

Classical Analysis and ODEs · Mathematics 2017-01-31 Christian Berg , Ryszard Szwarc

Eigenvalue and eigenpair backward errors are computed for matrix pencils arising in optimal control. In particular, formulas for backward errors are developed that are obtained under block-structure-preserving and…

Numerical Analysis · Mathematics 2017-12-25 Christian Mehl , Volker Mehrmann , Punit Sharma

In this article we study the structured distance to singularity for a nonsingular matrix $A\in\mathbb{C}^{n\times n}$, with a prescribed linear structure $\mathcal{S}$ (for instance, a sparsity pattern, or a real Toeplitz structure), i.e.,…

Numerical Analysis · Mathematics 2026-03-06 Miryam Gnazzo , Nicola Guglielmi , Federico Poloni , Stefano Sicilia

An asymptotic expression of the orthonormal polynomials $\mathcal{P}_{N}(z)$ as $N\rightarrow\infty$, associated with the singularly perturbed Laguerre weight $w_{\alpha}(x;t)=x^{\alpha}{\rm…

Mathematical Physics · Physics 2020-06-12 Mengkun Zhu , Yang Chen , Chuanzhong Li

In this paper we investigate regular patterns of matrix elements of the nuclear shell model Hamiltonian $H$, by sorting the diagonal matrix elements from the smaller to larger values. By using simple plots of non-zero matrix elements and…

Nuclear Theory · Physics 2014-11-21 J. J. Shen , Y. M. Zhao , A. Arima

We develop a new algorithm to compute determinants of all possible Hankel matrices made up from a given finite length sequence over a finite field. Our algorithm fits within the dynamic programming paradigm by exploiting new recursive…

Cryptography and Security · Computer Science 2022-01-04 Claude Gravel , Daniel Panario , Bastien Rigault

The rectangular multiparameter eigenvalue problem (RMEP) involves rectangular coefficient matrices (usually with more rows than columns) and may potentially have no solution in its original form. A minimal perturbation framework is proposed…

Numerical Analysis · Mathematics 2025-08-11 Shanheng Han , Lei-Hong Zhang , Ren-Cang Li

In the field of structural engineering analysis, a common requirement is to calculate the modal frequencies of a structure that has undergone an update, either naturally (such as from material degradation), or due to man-made influences (by…

Optimization and Control · Mathematics 2020-08-25 P. Cheema , M. M. Alamdari , G. A. Vio

Let $H\_0, ..., H\_n$ be $m \times m$ matrices with entries in $\QQ$ and Hankel structure, i.e. constant skew diagonals. We consider the linear Hankel matrix $H(\vecx)=H\_0+\X\_1H\_1+...+\X\_nH\_n$ and the problem of computing sample points…

Symbolic Computation · Computer Science 2015-02-10 Didier Henrion , Simone Naldi , Mohab Safey El Din

First, we derive explicit computable expressions of structured backward errors of approximate eigenelements of structured matrix polynomials including symmetric, skew-symmetric, Hermitian, skew-Hermitian, even and odd polynomials. We also…

Numerical Analysis · Mathematics 2009-07-16 Bibhas Adhikari , Rafikul Alam
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