EEE126 Linear Algebra
2024-2025 Spring
Weekly schedule
| Week | Part | Topic |
|---|---|---|
| 1 | Vectors | Vector fundamentals, linear functions |
| 2 | Vectors | Norm and distance, linear independence |
| 3 | Matrices | Matrix fundamentals, linear equations |
| 4 | Matrices | Matrix multiplication, matrix factorizations |
| 5 | Matrices | Matrix inverses, solving linear equations |
| 6 | Matrices | Determinant, eigenvalues, eigenvectors |
| 7 | Matrices | Diagonalization, dynamical systems |
| 8 | Midterm exam | |
| 9 | Matrices | Symmetric matrices, positive definiteness |
| 10 | Matrices | Singular value decomposition |
| 11 | Least squares | Fundamentals, data fitting, classification |
| 12 | Least squares | Multi-objective and constrained least squares |
| 13 | Least squares | Nonlinear least squares |
| 14 | Engineering applications | Introduction to optimization and machine learning |
| 15 | Engineering applications | Estimation and control, autonomous driving |
Resources
textbook: Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares (Boyd&Vandenberghe) (main textbook for the course)
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