Lectures related to Orthogonal Bases in R^2

Explains orthogonal projection onto a subspace and finding orthogonal bases using Gram-Schmidt procedure.

Explores orthogonal bases in vector spaces, explaining unique vector representations and spectral decomposition.

Covers diagonalization of matrices, eigenvectors, linear maps, and least squares method.

Covers vector spaces, operations, and linear independence with examples from polynomials and functions.

Covers linear independence, bases, and coordinate systems with examples and theorems.

Covers matrix operations, scalar product, orthogonality, and bases in vector spaces.