Orthogonal Projection: Theory and Applications

Related lectures (25)

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

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

Explains orthogonal families, bases, and projections in vector spaces.

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

Explores orthogonal complement and projection theorems in vector spaces.

Explores orthogonality, norms, and distances in vector spaces for solving linear systems.

Explains linear independence, bases, and dimension in vector spaces, including the importance of the order of vectors in a basis.

Covers orthogonal projections, rectors, norms, and geometric observations in vector spaces.

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

Covers the basics of linear algebra, emphasizing the identification of subspaces through key properties.