Show simple item record

dc.contributor.advisorSingh, Pravin.
dc.contributor.advisorSingh, Virath Sewnath.
dc.creatorKhambule, Pretty Nombuyiselo.
dc.date.accessioned2018-10-15T12:18:58Z
dc.date.available2018-10-15T12:18:58Z
dc.date.created2018
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/10413/15642
dc.descriptionMaster of Science in Applied Mathematics, University of KwaZulu-Natal, Westville, 2018.en_US
dc.description.abstractEigenvalues are characteristic of linear operators. Once the spectrum of a matrix is known then its Jordan Canonical form can be determined which simplifies the un- derstanding of the matrix. For large matrices and spectral analysis sometimes it is only necessary to know the eigenvalues of smallest and largest absolute values. Hence we consider various strategies of bounding the spectrum in the complex plane. Such bounds may be numerically improved by various algorithms. The minimal and maximal eigenvalues are crucial to determine the condition number of linear systems.en_US
dc.language.isoen_ZAen_US
dc.subject.otherEigenvalues.en_US
dc.subject.otherMatrices.en_US
dc.subject.otherJordan canonical.en_US
dc.subject.otherSpectral analysis.en_US
dc.subject.otherSpectrum.en_US
dc.titleEigenvalue bounds for matrices.en_US
dc.typeThesisen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record