Results 11 to 20 of about 128,344 (265)

Nonlinear Eigenvalue Problems with Specified Eigenvalues [PDF]

open access: yesSIAM Journal on Matrix Analysis and Applications, 2014
This work considers eigenvalue problems that are nonlinear in the eigenvalue parameter. Given such a nonlinear eigenvalue problem T, we are concerned with finding the minimal backward error such that T has a set of prescribed eigenvalues with prescribed algebraic multiplicities.
Michael Karow   +2 more
openaire   +4 more sources

Generalized eigenvalue problems with specified eigenvalues [PDF]

open access: yesIMA Journal of Numerical Analysis, 2013
We consider the distance from a (square or rectangular) matrix pencil to the nearest matrix pencil in 2-norm that has a set of specified eigenvalues. We derive a singular value optimization characterization for this problem and illustrate its usefulness for two applications.
D. Kressner   +3 more
openaire   +5 more sources

Guaranteed Eigenvalue Bounds for the Steklov Eigenvalue Problem [PDF]

open access: yesSIAM Journal on Numerical Analysis, 2019
To provide mathematically rigorous eigenvalue bounds for the Steklov eigenvalue problem, an enhanced version of the eigenvalue estimation algorithm developed by the third author is proposed, which removes the requirements of the positive definiteness of bilinear forms in the formulation of eigenvalue problems.
Chun'guang You, Hehu Xie, Xuefeng Liu
openaire   +3 more sources

Fusing Eigenvalues [PDF]

open access: yesICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
In this paper, we propose a new regularized (penalized) co-variance matrix estimator which encourages grouping of the eigenvalues by penalizing large differences (gaps) between successive eigenvalues. This is referred to as fusing eigenval-ues (eFusion), The proposed penalty function utilizes Tukey's biweight function that is widely used in robust ...
Ollila, Esa   +4 more
openaire   +3 more sources

Fractional eigenvalues [PDF]

open access: yesCalculus of Variations and Partial Differential Equations, 2013
We study a non-local eigenvalue problem related to the fractional Sobolev spaces for large values of p and derive the limit equation as p goes to infinity. Its viscosity solutions have many interesting properties and the eigenvalues exhibit a strange behaviour.
Lindgren, Erik, Lindqvist, Peter
openaire   +2 more sources

Bicliques and Eigenvalues [PDF]

open access: yesJournal of Combinatorial Theory, Series B, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +4 more sources

More on signed graphs with at most three eigenvalues [PDF]

open access: yes, 2021
We consider signed graphs with just 2 or 3 distinct eigenvalues, in particular (i) those with at least one simple eigenvalue, and (ii) those with vertexdeleted subgraphs which themselves have at most 3 distinct eigenvalues. We also construct new examples
StaniĆ, Zoran   +4 more
core   +1 more source

Eigenvalue and Generalized Eigenvalue Problems: Tutorial

open access: yesCoRR, 2019
This paper is a tutorial for eigenvalue and generalized eigenvalue problems. We first introduce eigenvalue problem, eigen-decomposition (spectral decomposition), and generalized eigenvalue problem. Then, we mention the optimization problems which yield to the eigenvalue and generalized eigenvalue problems. We also provide examples from machine learning,
Benyamin Ghojogh   +2 more
openaire   +2 more sources

Lassoing eigenvalues

open access: yesBiometrika, 2020
Summary The properties of penalized sample covariance matrices depend on the choice of the penalty function. In this paper, we introduce a class of nonsmooth penalty functions for the sample covariance matrix and demonstrate how their use results in a grouping of the estimated eigenvalues.
Tyler, David E., Yi, Mengxi
openaire   +2 more sources

Eigenvalue Decomposition of a Parahermitian Matrix: Extraction of Analytic Eigenvalues [PDF]

open access: yesIEEE Transactions on Signal Processing, 2021
An analytic parahermitian matrix admits an eigenvalue decomposition (EVD) with analytic eigenvalues and eigenvectors except in the case of multiplexed data. In this paper, we propose an iterative algorithm for the estimation of the analytic eigenvalues.
Stephan Weiss 0001   +2 more
openaire   +3 more sources

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