Covers the representation of signals in vector spaces and inner product spaces, including the Projection Theorem.
Explores equivalence in vector spaces, covering conditions for statements to be considered equivalent and properties of algebraic bases.
Introduces linear applications, span, kernels, and images in vector spaces with illustrative examples and theorems.
Covers the basics of linear algebra, emphasizing the identification of subspaces through key properties.
Explores curves in the oriented plane, discussing orientation, vector spaces, equivalence relations, and curvature of regular curves.
Explains orthogonality and characters in group representations, including equivalence classes and vector space dimensions.
Covers determining vector spaces, calculating kernels and images, defining bases, and discussing subspaces and vector spaces.
