Singular Values: Definitions and Properties

Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.

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

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.

Covers the process of diagonalizing matrices, focusing on symmetric matrices and the spectral theorem.