DSP Blockset | ![]() ![]() |
Solve the equation SX=B for X when S is a square Hermitian positive definite matrix.
Library
Math Functions / Matrices and Linear Algebra / Linear System Solvers
Description
The LDL Solver block solves the linear system SX=B by applying LDL factorization to the matrix at the S
port, which must be square (M-by-M) and Hermitian positive definite. Only the diagonal and lower triangle of the matrix are used, and any imaginary component of the diagonal entries is disregarded. The input to the B
port is the right-hand side M-by-N matrix, B. The output is the unique solution of the equations, M-by-N matrix X, and is always sample-based.
A length-M 1-D vector input for right-hand side B is treated as an M-by-1 matrix.
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:
Algorithm
The LDL algorithm uniquely factors the Hermitian positive definite input matrix S as
where L is a lower triangular square matrix with unity diagonal elements, D is a diagonal matrix, and L* is the Hermitian (complex conjugate) transpose of L.
is solved for X by the following steps:
Dialog Box
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
Autocorrelation LPC |
DSP Blockset |
Cholesky Solver |
DSP Blockset |
LDL Factorization |
DSP Blockset |
LDL Inverse |
DSP Blockset |
Levinson-Durbin |
DSP Blockset |
LU Solver |
DSP Blockset |
QR Solver |
DSP Blockset |
See Solving Linear Systems for related information. Also see Linear System Solvers for a list of all the blocks in the Linear System Solvers library.
![]() | LDL Inverse | Least Squares Polynomial Fit | ![]() |