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Related lectures (28)

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Covers the Gram-Schmidt algorithm for orthonormal bases in vector spaces.

Explores landmarks, coordinates, vectors, coplanarity, Cartesian equations, and geometric rules in space.

Covers attitude and orientation in rotations, including small angles and orthonormal properties.

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

Covers signal representations using scaling functions and orthonormal properties.

Explores orthonormal bases in Hilbert spaces, discussing their properties and generation using the Gram-Schmidt method.

Introduces scalars and vectors, explaining their properties and mathematical operations.

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

Discusses eigenfunctions of Hermitian operators in quantum chemistry and the quantization of energy levels.

Explores approximating functions with polynomials in inner product spaces, focusing on degree 2 and cosine functions.