Concept information
Preferred term
Gram-Schmidt process
Definition(s)
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In mathematics, particularly linear algebra and numerical analysis, the Gram–Schmidt process or Gram-Schmidt algorithm is a method for orthonormalizing a set of vectors in an inner product space, most commonly the Euclidean space Rn equipped with the standard inner product. The Gram–Schmidt process takes a finite, linearly independent set of vectors S = {v1, ..., vk} for k ≤ n and generates an orthogonal set S′ = {u1, ..., uk} that spans the same k-dimensional subspace of Rn as S.
(Wikipedia, The Free Encyclopedia, https://en.wikipedia.org/wiki/Gram%E2%80%93Schmidt_process)
Broader concept(s)
In other languages
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French
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algorithme de Gram-Schmidt
URI
http://data.loterre.fr/ark:/67375/PSR-SG5KGTBD-C
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