Decomposition Spectral: Symmetric Matrices

This lecture covers the decomposition of symmetric matrices into eigenvalues and eigenvectors, leading to the spectral theorem. It explains how a symmetric matrix can be diagonalized orthogonally using an orthogonal matrix P, resulting in a diagonal matrix D. The lecture also discusses the properties of eigenvalues, eigenvectors, and the orthogonality of the eigenspaces.