Lectures related to Balanced Realization: SISO Case

Covers linear systems, diagonal and triangular matrices, and LU factorization.

Discusses properties of symmetric matrices and the Spectral Theorem.

Covers the design of SISO polynomial controllers using concepts such as the Sylvester matrix and model matching.

Explores Singular Value Decomposition, low-rank approximation, fundamental subspaces, and matrix norms.

Explores the Jacobi method and diagonalization techniques, including similarity transformation, power methods, and QR decomposition.

Explains eigenvalues and eigenvectors of symmetric matrices and their properties.