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To understand the solution of a linear, time-invariant differential-algebraic equation, one must analyze a matrix pencil (A,E) with singular E. Even when this pencil is stable (all its finite eigenvalues fall in the left-half plane), the…

Numerical Analysis · Mathematics 2017-06-29 Mark Embree , Blake Keeler

We study ill-conditioned positive definite matrices that are disturbed by the sum of $m$ rank-one matrices of a specific form. We provide estimates for the eigenvalues and eigenvectors. When the condition number of the initial matrix tends…

Numerical Analysis · Mathematics 2024-03-13 Armand Gissler , Anne Auger , Nikolaus Hansen

The eigenproblem of low-rank updated matrices are of crucial importance in many applications. Recently, an upper bound on the number of distinct eigenvalues of a perturbed matrix was established. The result can be applied to estimate the…

Numerical Analysis · Mathematics 2017-08-14 Yunjie Wang , Gang Wu

An upper bound for the number of distinct eigenvalues of a perturbed matrix has been recently established by P. E. Farrell [1, Theorem 1.3]. The estimate is the central result in Farrell's work and can be applied to estimate the number of…

Numerical Analysis · Mathematics 2016-10-18 Xuefeng Xu

We consider a matrix pencil whose coefficients depend on a positive parameter $\epsilon$, and have asymptotic equivalents of the form $a\epsilon^A$ when $\epsilon$ goes to zero, where the leading coefficient $a$ is complex, and the leading…

Spectral Theory · Mathematics 2007-05-23 Marianne Akian , Ravindra Bapat , Stephane Gaubert

When computing the eigenstructure of matrix pencils associated with the passivity analysis of perturbed port-Hamiltonian descriptor system using a structured generalized eigenvalue method, one should make sure that the computed spectrum…

Optimization and Control · Mathematics 2020-05-12 Volker Mehrmann , Paul Van Dooren

In this text, based on elementary computations, we provide a perturbative expansion of the coordinates of the eigenvectors of a Hermitian matrix of large size perturbed by a random matrix with small operator norm whose entries in the…

Probability · Mathematics 2020-03-19 Florent Benaych-Georges , Nathanaël Enriquez , Alkéos Michaïl

The numerical solution of the generalized eigenvalue problem for a singular matrix pencil is challenging due to the discontinuity of its eigenvalues. Classically, such problems are addressed by first extracting the regular part through the…

Numerical Analysis · Mathematics 2024-07-17 Daniel Kressner , Bor Plestenjak

The matrix pencil method is an eigenvalue based approach for the parameter identification of sparse exponential sums. We derive a reconstruction algorithm for multivariate exponential sums that is based on simultaneous diagonalization.…

Numerical Analysis · Mathematics 2018-05-17 Martin Ehler , Stefan Kunis , Thomas Peter , Christian Richter

The standard approach for finding eigenvalues and eigenvectors of matrix polynomials starts by embedding the coefficients of the polynomial into a matrix pencil, known as linearization. Building on the pioneering work of Nakatsukasa and…

Numerical Analysis · Mathematics 2018-08-15 Javier Perez

We propose an iterative method to find pointwise growth exponential growth rates in linear problems posed on essentially one-dimensional domains. Such pointwise growth rates capture pointwise stability and instability in extended systems…

Numerical Analysis · Mathematics 2022-08-30 Arnd Scheel

Loewner matrix pencils play a central role in the system realization theory of Mayo and Antoulas, an important development in data-driven modeling. The eigenvalues of these pencils reveal system poles. How robust are the poles recovered via…

Numerical Analysis · Mathematics 2019-10-29 Mark Embree , A. Cosmin Ionita

We consider a pencil of matrix Sturm-Liouville operators on a finite interval. We study properties of its spectral characteristics and inverse problems that consist in recovering of the pencil by the spectral data: eigenvalues and…

Spectral Theory · Mathematics 2015-09-22 Natalia Bondarenko

We consider the eigenvalues and eigenvectors of finite, low rank perturbations of random matrices. Specifically, we prove almost sure convergence of the extreme eigenvalues and appropriate projections of the corresponding eigenvectors of…

Probability · Mathematics 2012-03-19 Florent Benaych-Georges , Raj Rao Nadakuditi

Estimating eigenvectors and low-dimensional subspaces is of central importance for numerous problems in statistics, computer science, and applied mathematics. This paper characterizes the behavior of perturbed eigenvectors for a range of…

Statistics Theory · Mathematics 2018-09-14 Joshua Cape , Minh Tang , Carey E. Priebe

We perturb a real matrix $A$ of full column rank, and derive lower bounds for the smallest singular values of the perturbed matrix, in terms of normwise absolute perturbations. Our bounds, which extend existing lower-order expressions,…

Numerical Analysis · Mathematics 2024-02-22 Christos Boutsikas , Petros Drineas , Ilse C. F. Ipsen

In a previous paper (J. Phys. A 36, 11807 (2003)), we introduced the `asymptotic iteration method' for solving second-order homogeneous linear differential equations. In this paper, we study perturbed problems in quantum mechanics and we…

Mathematical Physics · Physics 2009-11-11 Hakan Ciftci , Richard L. Hall , Nasser Saad

In this paper, we present perturbed law-based sensitivity indices and how to adapt them for quantile-oriented sensitivity analysis. We exhibit a simple way to compute these indices in practice using an importance sampling estimator for…

Statistics Theory · Mathematics 2017-07-06 Roman Sueur , Bertrand Iooss , Thibault Delage

Eigensolvers involving complex moments can determine all the eigenvalues in a given region in the complex plane and the corresponding eigenvectors of a regular linear matrix pencil. The complex moment acts as a filter for extracting…

Numerical Analysis · Mathematics 2021-09-22 Keiichi Morikuni

We present a randomized, inverse-free algorithm for producing an approximate diagonalization of any $n \times n$ matrix pencil $(A,B)$. The bulk of the algorithm rests on a randomized divide-and-conquer eigensolver for the generalized…

Numerical Analysis · Mathematics 2024-12-11 James Demmel , Ioana Dumitriu , Ryan Schneider
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