Lectures related to Diagonalization by Blocks

Explores eigenvalues and eigenvectors, demonstrating their importance in linear algebra and their application in solving systems of equations.

Covers the decomposition of a matrix into its eigenvalues and eigenvectors, the orthogonality of eigenvectors, and the normalization of vectors.

Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.

Explores the diagonalization of matrices through similarity transformations and the significance of this process in linear algebra.

Covers the Singular Value Decomposition theorem and its application in decomposing matrices.