Lectures related to Linear Algebra: Spectral Decomposition

Explores eigenvalues and eigenvectors in matrix transformations, essential for understanding mathematical and real-world systems.

Explores the diagonalization of symmetric matrices through orthogonal decomposition and the spectral theorem.

Explores the canonical basis in linear algebra, focusing on matrix representation, diagonalizability, and characteristic polynomials.

Covers matrix eigenvalues, eigenvectors, and their linear independence.

Covers the second criterion of diagonalization and similar matrices in linear applications.