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algebra > linear algebra > vector space > Gram-Schmidt process

Terme préférentiel

Gram-Schmidt process  

Définition(s)

  • 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)

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http://data.loterre.fr/ark:/67375/PSR-SG5KGTBD-C

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