Orthogonal Bases and Projection

Related lectures (22)

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

Covers scalar products, orthogonal vectors, norms, and projections in vector spaces, emphasizing orthonormal families of vectors.

Covers linear applications, diagonalizable matrices, eigenvectors, and orthogonal subspaces in R^n.

Covers the theorems related to orthogonal projection and orthonormal bases.

Introduces orthogonal families, orthonormal bases, and projections in linear algebra.

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

Covers the concept of orthogonal complement and projection in vector spaces.

Explains orthogonal projection in linear algebra, focusing on transforming non-orthogonal bases into orthogonal ones.

Explains orthogonal matrices, Gram-Schmidt process, and best vector approximation in subspaces.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.