Difference between revisions of "Manuals/calci/CHOLESKYFACTORIZATION"

From ZCubes Wiki
Jump to navigation Jump to search
(Created page with "<div style="font-size:30px">'''CHOLESKYFACTORIZATION(Matrix)'''</div><br/> *<math>Matrix</math> is the array of numeric elements ==Description== *This function gives the val...")
 
Line 46: Line 46:
 
*If the matrix A is Hermitian and positive semi-definite, then it still has a decomposition of the form A = LL^T if the diagonal entries of L are allowed to be zero.
 
*If the matrix A is Hermitian and positive semi-definite, then it still has a decomposition of the form A = LL^T if the diagonal entries of L are allowed to be zero.
 
*Also A can be written as LL^T for some invertible L, lower triangular or otherwise, then A is Hermitian and positive definite.
 
*Also A can be written as LL^T for some invertible L, lower triangular or otherwise, then A is Hermitian and positive definite.
 +
 +
==Examples==
 +
1. CHOLESKYFACTORIZATION([[25, 15, -5],[15, 18, 0],[ -5, 0, 11]])
 +
{| class="wikitable"
 +
|+Result
 +
|-
 +
| 5 || 0 || 0
 +
|-
 +
| 3 || 3 || 0
 +
|-
 +
| -1 || 1 || 3
 +
|}
 +
2. CHOLESKYFACTORIZATION([[8,14],[10,32]])
 +
{| class="wikitable"
 +
|+Result
 +
|-
 +
| 2.8284271247461903 || 0
 +
|-
 +
| 3.5355339059327373|| 4.415880433163924
 +
|}

Revision as of 15:38, 11 July 2017

CHOLESKYFACTORIZATION(Matrix)


  • is the array of numeric elements

Description

  • This function gives the value of Cholesky factorization.
  • It is called Cholesky Decomposition or Cholesky Factorization.
  • In , is the set of values.
  • The Cholesky Factorization is only defined for symmetric or Hermitian positive definite matrices.
  • Every positive definite matrix A can be factored as =
 is lower triangular with positive diagonal elements
 is is the conjugate transpose value of 
  • Every Hermitian positive-definite matrix has a unique Cholesky decomposition.
  • Here , is set of values to find the factorization value.
  • Partition matrices in = is

Algorithm

  1. Determine and
  2. = =
  3. Compute from
  4. =
    • this is a Cholesky Factorization of order
  • If the matrix A is Hermitian and positive semi-definite, then it still has a decomposition of the form A = LL^T if the diagonal entries of L are allowed to be zero.
  • Also A can be written as LL^T for some invertible L, lower triangular or otherwise, then A is Hermitian and positive definite.

Examples

1. CHOLESKYFACTORIZATION([[25, 15, -5],[15, 18, 0],[ -5, 0, 11]])

Result
5 0 0
3 3 0
-1 1 3

2. CHOLESKYFACTORIZATION([[8,14],[10,32]])

Result
2.8284271247461903 0
3.5355339059327373 4.415880433163924