Vector Spaces in R2 and R3

Related lectures (25)

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Covers vector spaces, bases, and decomposition of vectors in R³.

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.

Explores vector planes intersection, proportional vectors, and bases in IR3, including canonical bases and coordinate transformations.

Covers orthogonal projection, spectral decomposition, Gram-Schmidt process, and matrix factorization.

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

Covers the reduction of a linear application and finding corresponding reduced forms and bases.

Covers the concept of interesting subspaces related to matrices and the change of basis matrix.

Explores linear applications, vector spaces, kernels, and invertibility in linear algebra.

Covers fundamental concepts in linear algebra, including linear equations, matrix operations, determinants, and vector spaces.

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