Lectures related to Untitled | EPFL Graph Search

Explains methods for finding eigenvalues in linear algebra through examples.

Covers the diagonalization of linear transformations in R^3, exploring properties and examples.

Covers the concept of Singular Value Decomposition (SVD) for compressing information in matrices and images.

Explores diagonalization conditions, bases by eigenvectors, and generalization of concepts.

Explores matrix similarity, diagonalization, characteristic polynomials, eigenvalues, and eigenvectors in linear algebra.

Explains the inertia tensor, main axes, principal moments, and balancing of rotating solids.

Explores the criterion for matrix invertibility and the calculation of the inverse.

Explains the diagonalization of matrices, criteria, and significance of distinct eigenvalues.