BibTeX
@MISC{Stewart88stochasticperturbation,
author = {G. W. Stewart},
title = {Stochastic Perturbation Theory},
year = {1988}
}
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Abstract
. In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a first-order perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variation in the perturbed quantity. Up to the higher-order terms that are ignored in the expansion, these statistics tend to be more realistic than perturbation bounds obtained in terms of norms. The technique is applied to a number of problems in matrix perturbation theory, including least squares and the eigenvalue problem. Key words. perturbation theory, random matrix, linear system, least squares, eigenvalue, eigenvector, invariant subspace, singular value AMS(MOS) subject classifications. 15A06, 15A12, 15A18, 15A52, 15A60 1. Introduction. Let A be a matrix and let F be a matrix valued function of A. Two principal problems of matrix perturbation theory are the following. Given a matrix E, pr...
Keyphrases
stochastic perturbation theory matrix perturbation theory perturbed quantity singular value am higher-order term subject classification random matrix invariant subspace key word eigenvalue problem perturbation theory paper classical matrix perturbation theory probabilistic point first-order perturbation expansion linear system principal problem perturbation bound
