IC(Choleskyfactorization).docVIP

 TOC \o 1-3 \h \z \u  HYPERLINK \l _Toc270969473 1.1 LLT算法  PAGEREF _Toc270969473 \h 1  HYPERLINK \l _Toc270969474 1.2 LDLT算法  PAGEREF _Toc270969474 \h 1  LLT算法 LL^T算法For For End for i For For End for i End for k For End for i End for j LDLT算法 参考算法： /wiki/Cholesky_decomposition Avoiding taking square roots An alternative form is the factorization HYPERLINK /wiki/Cholesky_decomposition \l cite_note-1#cite_note-1 [2] This form eliminates the need to take square roots. When A is positive definite the elements of the diagonal matrix D are all positive. However this factorization can be used for any square, symmetrical matrix. If A is real, the following recursive relations apply for the entries of D and L: For complex Hermitian matrix A, the following formula applies: The LDLT and LLT factorizations (note that L is different between the two) may be easily related: The last expression is the product of a lower triangular matrix and its transpose, as is the LLT factorization.  算法设计： /wiki /Cholesky_decomposition根据wiki得到算法的伪代码 For For End for i For //遍历L第j行所有元素 //确定(要提高效率需要再设个数组) 以前基于ITSOL的程序没有进行效率考虑. For //遍历L第k列部分元素 End for i End for k For End for i End for j