Lectures related to Primitive Matrices and Spectral Properties in Networked Control Systems

Explains the diagonalization of matrices, criteria, and significance of distinct eigenvalues.

Explores the diagonalizability of symmetric matrices and their eigenvectors in an orthonormal basis.

Explores symmetric matrices, eigenvalues, eigenvectors, and the spectral theorem in linear algebra.

Explores the diagonalization of symmetric matrices and the orthogonality of eigenvectors.

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

Covers Canonical Correlation Analysis, a method to find relationships between two sets of variables.

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

Explains how to find free variables in matrix equations and analyze characteristic polynomials.