This lecture covers examples of symmetric matrices, properties of orthogonal matrices, and the spectral decomposition of symmetric matrices. It discusses eigenvectors, eigenvalues, and the orthogonality between eigenspaces. The lecture also explores the consequences of symmetric matrices being orthogonal.
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