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In linear algebra, orthogonalization is the process of finding a set of orthogonal vectors that span a particular subspace. Formally, starting with a linearly independent set of vectors {v1, ... , vk} in an inner product space (most commonly the Euclidean space Rn), orthogonalization results in a set of orthogonal vectors {u1, ... , uk} that generate the same subspace as the vectors v1, ... , vk. Every vector in the new set is orthogonal to every other vector in the new set; and the new set and the old set have the same linear span.

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  • Orthogonalisierungsverfahren (de)
  • Orthogonalization (en)
  • 直交化 (ja)
  • Ortogonalização (pt)
  • Ортогонализация (ru)
  • 正交化 (zh)
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  • 直交化(ちょっこうか)とは、線型空間上にあるベクトルの組から、互いに直交するベクトルの組を生成することである。 (ja)
  • Ортогонализация ― процесс построения по заданному базису линейного пространства некоторого ортогонального базиса, который имеет ту же самую линейную оболочку. Ввиду удобства и важности ортогональных базисов в различных задачах, важны и процессы ортогонализации. (ru)
  • 线性代数中的正交化指的是:从内积空间(包括常见的欧几里得空间)中的一组线性无关向量v1,...,vk出发,得到同一个子空间上两两正交的向量组u1,...,uk。 如果还要求正交化后的向量都是单位向量,那么称为标准正交化。 一般在数学分析中采用格拉姆-施密特正交化作正交化的计算。在编程计算时,格拉姆-施密特正交化的数值稳定性不高,所以常用更稳定的豪斯霍尔德变换代替。另外,相对于豪斯霍尔德变换在最后直接生成所有的向量,格拉姆-施密特方法在第i步产生第i个向量,因此后者可用迭代法编写。对于含有零元素较多的向量组(例如稀疏矩阵的QR分解),还会采用吉文斯旋转。 (zh)
  • Mit Orthogonalisierungsverfahren bezeichnet man in der Mathematik Algorithmen, die aus einem System linear unabhängiger Vektoren ein Orthogonalsystem erzeugen, das den gleichen Untervektorraum aufspannt. mit einer orthogonalen Matrix und einer Dreiecksmatrix zu erzeugen. Die Spaltenvektoren der Matrix sind dann die orthogonalisierten Spaltenvektoren der Matrix . Hauptsächlich erhält man aber eine stabile Methode zum Lösen linearer Gleichungssysteme. (de)
  • In linear algebra, orthogonalization is the process of finding a set of orthogonal vectors that span a particular subspace. Formally, starting with a linearly independent set of vectors {v1, ... , vk} in an inner product space (most commonly the Euclidean space Rn), orthogonalization results in a set of orthogonal vectors {u1, ... , uk} that generate the same subspace as the vectors v1, ... , vk. Every vector in the new set is orthogonal to every other vector in the new set; and the new set and the old set have the same linear span. (en)
  • Em álgebra linear, ortogonalização é o processo de encontrar um conjunto de vetor ortogonal que gera um subespaço específico. Formalmente, começando com um conjunto linearmente independente de vetores {v1, ... , vk} em um espaço com produto interno (mais frequentemente o espaço euclidiano Rn), o processo de ortogonalização resulta em um conjunto de vetores ortogonais {u1, ... , uk} que geram o mesmo subespaço que os vetores v1, ... , vk. Todo vetor do novo conjunto é ortogonal a todos os demais vetores do novo conjunto; e o novo conjunto e o antigo possuem o mesmo espaço gerado. (pt)
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  • Mit Orthogonalisierungsverfahren bezeichnet man in der Mathematik Algorithmen, die aus einem System linear unabhängiger Vektoren ein Orthogonalsystem erzeugen, das den gleichen Untervektorraum aufspannt. Das bekannteste Verfahren dieser Art ist das Gram-Schmidtsche Orthogonalisierungsverfahren. Dieses kann man für beliebige Vektoren aus einem Prähilbertraum verwenden. Oftmals ist die Orthogonalisierung von Vektoren zwar namensgebend, aber nicht das eigentliche Ziel solcher Verfahren. So benutzt man in der Numerischen Mathematik Orthogonalisierungsverfahren wie die Householder-Transformation oder die Givens-Rotation hauptsächlich um eine QR-Zerlegung mit einer orthogonalen Matrix und einer Dreiecksmatrix zu erzeugen. Die Spaltenvektoren der Matrix sind dann die orthogonalisierten Spaltenvektoren der Matrix . Hauptsächlich erhält man aber eine stabile Methode zum Lösen linearer Gleichungssysteme. Zur Rückführung eines verallgemeinerten Eigenwertproblems auf ein spezielles Eigenwertproblem kann man Symmetrische Orthogonalisierung sowie verwenden. (de)
  • In linear algebra, orthogonalization is the process of finding a set of orthogonal vectors that span a particular subspace. Formally, starting with a linearly independent set of vectors {v1, ... , vk} in an inner product space (most commonly the Euclidean space Rn), orthogonalization results in a set of orthogonal vectors {u1, ... , uk} that generate the same subspace as the vectors v1, ... , vk. Every vector in the new set is orthogonal to every other vector in the new set; and the new set and the old set have the same linear span. In addition, if we want the resulting vectors to all be unit vectors, then we normalize each vector and the procedure is called orthonormalization. Orthogonalization is also possible with respect to any symmetric bilinear form (not necessarily an inner product, not necessarily over real numbers), but standard algorithms may encounter division by zero in this more general setting. (en)
  • 直交化(ちょっこうか)とは、線型空間上にあるベクトルの組から、互いに直交するベクトルの組を生成することである。 (ja)
  • Ортогонализация ― процесс построения по заданному базису линейного пространства некоторого ортогонального базиса, который имеет ту же самую линейную оболочку. Ввиду удобства и важности ортогональных базисов в различных задачах, важны и процессы ортогонализации. (ru)
  • Em álgebra linear, ortogonalização é o processo de encontrar um conjunto de vetor ortogonal que gera um subespaço específico. Formalmente, começando com um conjunto linearmente independente de vetores {v1, ... , vk} em um espaço com produto interno (mais frequentemente o espaço euclidiano Rn), o processo de ortogonalização resulta em um conjunto de vetores ortogonais {u1, ... , uk} que geram o mesmo subespaço que os vetores v1, ... , vk. Todo vetor do novo conjunto é ortogonal a todos os demais vetores do novo conjunto; e o novo conjunto e o antigo possuem o mesmo espaço gerado. Além disso, se o objetivo for obter vetores que são unitários, então o procedimento é chamado de ortonormalização. Também é possível realizar o processo de ortonormalização com relação a qualquer forma bilinear simétrica (não necessariamente um produto interno, e não necessariamente sobre os números reais), mas os algoritmos usuais podem se deparar com divisão por zero nesta situação mais geral. (pt)
  • 线性代数中的正交化指的是:从内积空间(包括常见的欧几里得空间)中的一组线性无关向量v1,...,vk出发,得到同一个子空间上两两正交的向量组u1,...,uk。 如果还要求正交化后的向量都是单位向量,那么称为标准正交化。 一般在数学分析中采用格拉姆-施密特正交化作正交化的计算。在编程计算时,格拉姆-施密特正交化的数值稳定性不高,所以常用更稳定的豪斯霍尔德变换代替。另外,相对于豪斯霍尔德变换在最后直接生成所有的向量,格拉姆-施密特方法在第i步产生第i个向量,因此后者可用迭代法编写。对于含有零元素较多的向量组(例如稀疏矩阵的QR分解),还会采用吉文斯旋转。 (zh)
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