This lecture introduces the concept of eigenvalues and eigenvectors for square matrices. Eigenvalues are values for which a matrix times a vector equals a scalar times the same vector. Eigenvectors are the vectors associated with eigenvalues. The lecture covers definitions, examples, consequences, and calculations of eigenvalues and eigenvectors, as well as characteristic polynomials. It also explains how to find eigenspaces associated with eigenvalues and provides examples of finding eigenspaces for different matrices.
This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.
Watch on Mediaspace