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Cholesky algorithm

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  • Cholesky decomposition — In linear algebra, the Cholesky decomposition or Cholesky triangle is a decomposition of a Hermitian, positive definite matrix into the product of a lower triangular matrix and its conjugate transpose. It was discovered by André Louis Cholesky… …   Wikipedia

  • Minimum degree algorithm — In numerical analysis the minimum degree algorithm is an algorithm used to permute the rows and columns of a symmetric sparse matrix before applying the Cholesky decomposition, to reduce the number of non zeros in the Cholesky factor. This… …   Wikipedia

  • Symbolic Cholesky decomposition — In the mathematical subfield of numerical analysis the symbolic Cholesky decomposition is an algorithm used to determine the non zero pattern for the L factors of a symmetric sparse matrix when applying the Cholesky decomposition or… …   Wikipedia

  • Incomplete Cholesky factorization — In numerical analysis, a field within mathematics, an incomplete Cholesky factorization of a symmetric positive definite matrix is a sparse approximation of the Cholesky factorization. Incomplete Cholesky factorization are often used as a… …   Wikipedia

  • Gauss–Newton algorithm — The Gauss–Newton algorithm is a method used to solve non linear least squares problems. It can be seen as a modification of Newton s method for finding a minimum of a function. Unlike Newton s method, the Gauss–Newton algorithm can only be used… …   Wikipedia

  • Skyline matrix — A skyline matrix, or a variable band matrix, is a form of a sparse matrix storage format for a square, banded (and typically symmetric) matrix that reduces the storage requirement of a matrix more than banded storage. In banded storage, all… …   Wikipedia

  • List of numerical analysis topics — This is a list of numerical analysis topics, by Wikipedia page. Contents 1 General 2 Error 3 Elementary and special functions 4 Numerical linear algebra …   Wikipedia

  • LU decomposition — In linear algebra, LU decomposition (also called LU factorization) is a matrix decomposition which writes a matrix as the product of a lower triangular matrix and an upper triangular matrix. The product sometimes includes a permutation matrix as… …   Wikipedia

  • Mehrotra predictor-corrector method — Mehrotra s predictor corrector method in optimization is an implementation of interior point methods. It was proposed in 1989 by Sanjay Mehrotra. [cite journal|last=Mehrotra|first=S.|title=On the implementation of a primal–dual interior point… …   Wikipedia

  • Mehrotra predictor–corrector method — Mehrotra s predictor–corrector method in optimization is an implementation of interior point methods. It was proposed in 1989 by Sanjay Mehrotra.[1] The method is based on the fact that at each iteration of an interior point algorithm it is… …   Wikipedia

  • Kalman filter — Roles of the variables in the Kalman filter. (Larger image here) In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kálmán. Its purpose is to use measurements observed over time, containing noise (random variations)… …   Wikipedia

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