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文件名称:resolution_gauss_descents
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In numerical analysis, LU decomposition (where LU stands for Lower Upper , and also called LU factorization) factors a matrix as the product of a lower triangular matrix and an upper triangular matrix. The product sometimes includes a permutation matrix as well. The LU decomposition can be viewed as the matrix form of Gaussian elimination. Computers usually solve square systems of linear equations using the LU decomposition, and it is also a key step when inverting a matrix, or computing the determinant of a matrix. The LU decomposition was introduced by mathematician Alan Turing.[1]-In numerical analysis, LU decomposition (where LU stands for Lower Upper , and also called LU factorization) factors a matrix as the product of a lower triangular matrix and an upper triangular matrix. The product sometimes includes a permutation matrix as well. The LU decomposition can be viewed as the matrix form of Gaussian elimination. Computers usually solve square systems of linear equations using the LU decomposition, and it is also a key step when inverting a matrix, or computing the determinant of a matrix. The LU decomposition was introduced by mathematician Alan Turing.[1]
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resolution_gauss_descents/resolution_gauss_descente.cpp
resolution_gauss_descents/resolution_gauss_descente.docx
resolution_gauss_descents/resolution_gauss_descente.exe
resolution_gauss_descents
resolution_gauss_descents/resolution_gauss_descente.docx
resolution_gauss_descents/resolution_gauss_descente.exe
resolution_gauss_descents
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