linear-algebra
Symmetric matrices and orthogonal diagonalization
taught
Taught in
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Eigenvalues, eigenvectors, and diagonalization
Advanced Linear Algebra
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Eigenvalues, eigenvectors, and diagonalization, revisited
Fourier Analysis
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Symmetric matrices and orthogonal diagonalization
Linear Algebra — Vectors, Matrices, and the Geometry of Data
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Eigenvalues, symmetric matrices, and quadratic forms, revisited
Optimization
Requires
Required by
- Circulant matrices are diagonalized by the DFT basis required
- Markov chains and steady states required
- The real spectral theorem required
Local knowledge map
Local knowledge map
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Solid arrows are required prerequisites; dashed are recommended or helpful. Lower rows are more foundational. Click any box to jump to that concept.