Discrete Vibratory Systems: Linear Analysis

Related lectures (28)

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Covers the calculation of eigenvalues and eigenvectors, emphasizing their significance and applications.

Explores Sylvester's Inertia Theorem, relating eigenvalues to diagonal entries in symmetric matrices.

Explores diagonalization in symmetric matrices, emphasizing orthogonality and orthonormal bases.

Covers the concept of balanced realization in the SISO case, focusing on system observability and controllability.

Explores stationary points, saddle points, symmetric matrices, and orthogonal properties in optimization.

Explores diagonalization of symmetric matrices and their eigenvalues, emphasizing orthogonal properties.

Explores spectral and singular value decompositions of matrices.

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

Discusses properties of symmetric matrices and the Spectral Theorem.

Covers the decomposition of matrices into triangular blocks and spectral decomposition.