Lectures related to Matrix Computations: Eigenvalues and Eigenvectors

Explores the diagonalization of symmetric matrices using eigenvectors and eigenvalues, emphasizing orthogonality and real eigenvalues.

Explores the application of matrices and eigendecompositions in networks.

Covers the reduction of a linear transformation in a 2-dimensional space to find a simpler matrix representation.

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

Explores the unique decomposition of matrices into diagonalizable and nilpotent parts, showcasing their properties and applications.

Covers the concept of diagonalizability of matrices and explores eigenvalues and eigenvectors.

Explores the diagonalization of matrices through eigenvectors and eigenvalues.