Quadratic Best Approximation

Related lectures (31)

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Covers the concept of 3D vector space, scalar product, bases, orthogonality, and projections.

Introduces orthogonal and orthonormal families in vector spaces with scalar products.

Explains orthogonal projection on a vector subspace in Euclidean space.

Introduces orthogonality between vectors, angles, and orthogonal complement properties in vector spaces.

Explores normal equations, pseudo-solutions, unique solutions, and symmetric matrices in linear algebra.

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

Explores the properties of orthonormal vectors in Euclidean space through key equations and demonstrations.

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

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

Covers the properties of Euclidean spaces, focusing on R^n and its applications in analysis.