Lectures related to Linear Algebra: Matrix Operations and Orthogonality

Covers mathematical concepts related to vector operations and geometry, including scalar product and vector norms.

Covers the representation of signals in vector spaces and inner product spaces, including the Projection Theorem.

Covers matrices, linear applications, vector spaces, and bijective functions.

Covers orthogonal vectors, unit vectors, and the Pythagorean theorem in R^m.

Covers the Gram-Schmidt algorithm for orthonormal bases in vector spaces.

Explores area determination, linear applications, matrix operations, and vector spaces.

Explores orthogonality between vectors and subspaces, demonstrating practical implications in matrix operations.

Covers the definition of norm, distance between vectors, and Cauchy-Schwarz inequality.