Orthogonal Matrices & Spectral Decomposition

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Explores spectral and singular value decompositions of matrices.

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

Covers examples of symmetric matrices and their properties, including eigenvectors and eigenvalues.

Explores symmetric matrices, their diagonalization, and properties like eigenvalues and eigenvectors.

Explores the spectral decomposition of symmetric matrices, including diagonalization and orthogonal basis change matrices.

Covers the decomposition of symmetric matrices into eigenvalues and eigenvectors.

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

Provides an overview of symmetric matrices, quadratic forms, and their applications in linear algebra and analysis.

Covers the properties and applications of orthogonal matrices.

Covers the concept of symmetric matrices, orthogonal bases, and eigenvectors.