EE263: Matrix Methods: Singular Value Decomposition

Lecture videos

• Video from the lectures is available on Canvas

Lecture slides

This list will be updated throughout the quarter. See here for a complete list of lecture slides from the previous offering of the course (Fall 2025). While the content is very similar, we may add or remove some topics, or adjust the order and structure in which we cover them.

1. Overview (annotated slides)

2. Linear functions (annotated slides)

3. Engineering examples (annotated slides)

4. Interpretations of linear equations (annotated slides)

5. Linear algebra review (annotated slides)

6. Range and null space (annotated slides)

7. Rank (annotated slides)

8. Orthogonality (annotated slides)

9. QR factorization (annotated slides)

10. Least squares (annotated slides)

11. Multi-objective least squares (annotated slides)

12. Least-norm solutions (annotated slides)

13. Eigenvalues and diagonalization (annotated slides, note on complex numbers)

14. Symmetric matrices and quadratic forms (annotated slides)

15. Ellipsoids (annotated slides)

16. Matrix norm (annotated slides)

17. Singular value decomposition (annotated slides)

18. Principal component analysis (annotated slides)

19. Probability review

20. Gaussians (annotated slides)

21. Conditional Gaussians (annotated slides)

22. MMSE estimation (annotated slides)

23. The linear model (annotated slides)

24. Spectral graph embedding (annotated slides)