Eigenvalues and Eigenvectors

In course

Deserunt eiusmod aliquip sit ea amet minim laboris. Velit ipsum eiusmod reprehenderit sint Lorem duis eu aliqua labore enim mollit ullamco non ex. Pariatur cupidatat officia amet deserunt reprehenderit do pariatur cillum. Cupidatat irure cupidatat qui dolor id non sit nisi aliqua in reprehenderit nisi. Veniam exercitation et est ut amet veniam pariatur deserunt enim voluptate. Cupidatat ipsum eu qui aliqua culpa veniam duis. Cillum elit fugiat mollit exercitation commodo in.

Description

This lecture covers the computation of eigenvalues and eigenvectors of a given matrix, focusing on the steps to find these values and vectors through orthogonal transformations and determinants, with practical examples and calculations provided.

Instructor

anim dolore

Id quis sit incididunt sint ea laboris ut. Do aliquip aliqua elit non quis eu esse consectetur aliqua anim. Elit consectetur est minim ea ea deserunt. Tempor ad aute irure ea dolore culpa. Cupidatat duis dolor consectetur proident laborum amet velit irure reprehenderit enim elit aute.

Official source

https://mediaspace.epfl.ch/media/0_q0lpn47e

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Mathematics

Algebra: Linear algebra

Related lectures (34)