Lectures related to Linear Applications Overview

Explores the concept of linear independence in vector spaces through definitions and illustrative examples.

Explores matrix representations of linear maps and their invariance, using examples and special cases.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

Covers the definition and examples of vector spaces, including subspaces and linear transformations.

Covers orthogonality, scalar products, orthogonal bases, and vector projection in detail.

Explains orthogonal projection and vector decomposition with examples in particle trajectory analysis.