Section 3: Geometric & Optimization Methods
Overview
Focus on orthogonality, projections, and optimization applications of linear algebra.
Topics Covered
Chapter 3: Orthogonality
- Orthogonal vectors and subspaces (3.1)
- Projections and least squares (3.3)
- Gram-Schmidt process (3.4)
- Fast Fourier Transform (3.5)
Chapter 6 (Selected)
- Minima, maxima, and saddle points (6.1)
- Finite Element Method (6.5)
Learning Objectives
- Master orthogonality concepts and applications
- Solve least squares problems
- Apply Gram-Schmidt orthogonalization
- Understand optimization in linear algebra context