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Cholesky Factoring Of A Matrix
 Syntax `cholesky(`B`)` `[C, p] = cholesky(`B`)` See Also svd , eigen , qred

Description
Returns an upper triangular matrix C that is a Cholesky factor for the matrix B; i.e., ```       H      C  C = B ```where B is a real, double-precision, or complex conjugate symmetric matrix and the superscript `H` denotes the complex conjugate transpose. The return value has the same type as B. ``` ```The matrix B is positive definite if ```       H      x  B x > 0 ```whenever `x` is a nonzero column vector with row dimension equal to the column dimension of B. If the argument p is not present and the matrix B is not positive definite, and error message will result. If the argument p is present and the matrix B is positive definite, p is the integer scalar zero. Otherwise, p is the smallest integer scalar such that `B(1::p, 1::p)` is not positive definite. In this case the return value C is a Cholesky factor for the upper left `(p-1)` by `(p-1)` block of B.

Example ```      B = {[2., 1.], [1., 2.]}      cholesky(B) ``` returns ```      {      [ 1.41421 , 0.707107 ]      [ 0 , 1.22474 ]      } ```
Mlmode
In Mlmode , this function is called `chol` instead of `cholesky`. If you continue the example above by entering ```      mlmode      chol(B) ``` O-Matrix will respond ```      {      [ 1.41421 , 0.707107 ]      [ 0 , 1.22474 ]      } ``` You can return to O-Matrix mode by entering ```      omatrix ```