Lecture
Orthogonal Projections and Best Approximation
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Description
This lecture covers the concept of orthogonal matrices, the Gram-Schmidt process, and the best approximation of a vector in a subspace. It explains how to find the closest vector in a subspace and how to orthogonalize a basis using the Gram-Schmidt algorithm.
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