文件名称:cholesky323232
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平均因子分解法,适用于正定矩阵First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square matrix X, the Cholesky decomposition of X is the factorization X=U U, where U is the square root matrix of X, and satisfies:
(1) U U = X
(2) U is upper triangular (that is, it has all zeros below the diagonal).
It seems that the assumption of positive definiteness is necessary. Actually, it is \"positive definite\" which guarantees the existence of such kind of decomposition.
(1) U U = X
(2) U is upper triangular (that is, it has all zeros below the diagonal).
It seems that the assumption of positive definiteness is necessary. Actually, it is \"positive definite\" which guarantees the existence of such kind of decomposition.
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下载文件列表
cholesky/Cholesky decomposition.txt
cholesky/Form1.frm
cholesky/Module1.bas
cholesky/_desktop.ini
cholesky/工程1.vbp
cholesky/工程1.vbw
cholesky
www.dssz.com.txt
cholesky/Form1.frm
cholesky/Module1.bas
cholesky/_desktop.ini
cholesky/工程1.vbp
cholesky/工程1.vbw
cholesky
www.dssz.com.txt
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