Gram-Schmidt Orthogonalization is a mathematical process used to convert a set of linearly independent vectors into an orthogonal set of vectors that span the same subspace. This technique is important because orthogonal vectors simplify many problems in linear algebra, especially when it comes to calculations involving projections and least squares approximations, which are often integral to power and inverse power methods.
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