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  2. Orthogonal Procrustes problem - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_Procrustes_problem

    The orthogonal Procrustes problem [1] is a matrix approximation problem in linear algebra.In its classical form, one is given two matrices and and asked to find an orthogonal matrix which most closely maps to .

  3. List of PDF software - Wikipedia

    en.wikipedia.org/wiki/List_of_PDF_software

    Default PDF and file viewer for GNOME; replaces GPdf. Supports addition and removal (since v3.14), of basic text note annotations. CUPS: Apache License 2.0: No No No Yes Printing system can render any document to a PDF file, thus any Linux program with print capability can produce PDF files Pdftk: GPLv2: No Yes Yes

  4. Numerical methods for linear least squares - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    The matrix X is subjected to an orthogonal decomposition, e.g., the QR decomposition as follows. = , where Q is an m×m orthogonal matrix (Q T Q=I) and R is an n×n upper triangular matrix with >. The residual vector is left-multiplied by Q T.

  5. TRIZ - Wikipedia

    en.wikipedia.org/wiki/TRIZ

    TRIZ flowchart Contradiction matrix 40 principles of invention, principles based on TRIZ. One tool which evolved as an extension of TRIZ was a contradiction matrix. [14] The ideal final result (IFR) is the ultimate solution of a problem when the desired result is achieved by itself.

  6. Cholesky decomposition - Wikipedia

    en.wikipedia.org/wiki/Cholesky_decomposition

    In linear algebra, the Cholesky decomposition or Cholesky factorization (pronounced / ʃ ə ˈ l ɛ s k i / shə-LES-kee) is a decomposition of a Hermitian, positive-definite matrix into the product of a lower triangular matrix and its conjugate transpose, which is useful for efficient numerical solutions, e.g., Monte Carlo simulations.

  7. Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Gaussian_elimination

    So there is a unique solution to the original system of equations. Instead of stopping once the matrix is in echelon form, one could continue until the matrix is in reduced row echelon form, as it is done in the table. The process of row reducing until the matrix is reduced is sometimes referred to as Gauss–Jordan elimination, to distinguish ...

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