Difference between revisions of "Manuals/calci/CHOLESKY"
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*Every Hermitian positive-definite matrix (and thus also every real-valued symmetric positive-definite matrix) has a unique Cholesky decomposition. | *Every Hermitian positive-definite matrix (and thus also every real-valued symmetric positive-definite matrix) has a unique Cholesky decomposition. | ||
*Here <math>CHOLESKY(arr)</math>, <math>arr</math> is set of values to find the factorization value. | *Here <math>CHOLESKY(arr)</math>, <math>arr</math> is set of values to find the factorization value. | ||
− | *Partition matrices in as <math>A</math> = <math>LL^{T}<math> (Please take the description from http://www.seas.ucla.edu/~vandenbe/103/lectures/chol.pdf ) | + | *Partition matrices in as <math>A</math> = <math>LL^{T}</math> (Please take the description from http://www.seas.ucla.edu/~vandenbe/103/lectures/chol.pdf ) |
==ZOS Section== | ==ZOS Section== |
Revision as of 05:44, 8 April 2015
CHOLESKY(arr)
- is the array of numeric elements
Description
- This function gives the value of Cholesky factorization.
- It is called Cholesky Decomposition or Cholesky Factorization.
- The Cholesky Factorization is only defined for symmetric or Hermitian positive definite matrices.
- Every positive definite matrix A can be factored as =
where
is lower triangular with positive diagonal elements is is the conjugate transpose value of
- Every Hermitian positive-definite matrix (and thus also every real-valued symmetric positive-definite matrix) has a unique Cholesky decomposition.
- Here , is set of values to find the factorization value.
- Partition matrices in as = (Please take the description from http://www.seas.ucla.edu/~vandenbe/103/lectures/chol.pdf )