Performs Cholesky factorization on a symmetric or Hermitian positive definite matrix.
A symmetric or Hermitian positive definite matrix.
This input accepts a 2D array of double-precision, floating point numbers or 2D array of complex double-precision, floating point numbers.
If the input matrix is not symmetric or Hermitian, this node uses only the upper triangular portion of the input matrix. If the input matrix is not positive definite, this node returns an error.
Default: Empty array
Error conditions that occur before this node runs.
The node responds to this input according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
Default: No error
The factored, upper triangular matrix.
Error information.
The node produces this output according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
The following equations show the factorization of the input matrix A for real cases and complex cases, respectively:
A = R T R
A = R H R
where A is the input matrix A, R is an upper triangular matrix, and all the diagonal elements of R are positive.
The Cholesky factorization exists only if the input matrix A is positive definite and either symmetric or Hermitian. If the input matrix A is not symmetric or Hermitian, this node uses only the upper triangular portion of the input matrix A. If the input matrix A is not positive definite, this node returns an error.
You can use Cholesky factorization to solve linear equations. For example, to solve the linear equation A x = b, where A is a positive symmetric matrix and A = R T R, first derive the following equations: R x = h and h = R -T b. Then use the triangular property of R to solve the equations.
Where This Node Can Run:
Desktop OS: Windows
FPGA: Not supported
Web Server: Not supported in VIs that run in a web application