| DSP Blockset | |
Compute the inverse of a Hermitian positive definite matrix using Cholesky factorization.
Library
Math Functions / Matrices and Linear Algebra / Matrix Inverses
Description
The Cholesky Inverse block computes the inverse of the Hermitian positive definite input matrix S by performing Cholesky factorization.
L is a lower triangular square matrix with positive diagonal elements and L* is the Hermitian (complex conjugate) transpose of L. Only the diagonal and upper triangle of the input matrix are used, and any imaginary component of the diagonal entries is disregarded. Cholesky factorization requires half the computation of Gaussian elimination (LU decomposition), and is always stable. The output is always sample-based.
The algorithm requires that the input be Hermitian positive definite. When the input is not positive definite, the block reacts with the behavior specified by the Non-positive definite input parameter. The following options are available:
Dialog Box
References
Golub, G. H., and C. F. Van Loan. Matrix Computations. 3rd ed. Baltimore, MD: Johns Hopkins University Press, 1996.
Supported Data Types
To learn how to convert to the above data types in MATLAB and Simulink, see Supported Data Types and How to Convert to Them.
See Also
| Cholesky Factorization |
DSP Blockset |
| Cholesky Solver |
DSP Blockset |
| LDL Inverse |
DSP Blockset |
| LU Inverse |
DSP Blockset |
| Pseudoinverse |
DSP Blockset |
inv |
MATLAB |
See Inverting Matrices for related information. Also see Matrix Inverses for a list of all the blocks in the Matrix Inverses library.
| | Cholesky Factorization | Cholesky Solver | |
