主要内容

线性代数

R2026b
求解线性方程组,对矩阵进行分解和求逆

DSP System Toolbox™ 系统线性代数模块使您能够在 Simulink® 中处理矩阵。例如,要通过莱文森-杜宾和乔列斯基方法求解一组线性方程,请使用 Levinson-Durbin 和 Cholesky Solver 模块。这些方法通常用于尤尔-沃克 AR 问题和线性预测编码等应用中。要将一个方阵分解为上三角和下三角部成分,请使用 LDL 分解和 LU 分解等方法。要对矩阵求逆,请使用乔列斯基分解、LDL 分解和 LU 分解等方法。有关所有支持的方法和 DSP System Toolbox 中实现这些方法的对应模块的摘要,请参阅Linear Algebra and Least Squares。

模块

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Cholesky Factorization blockCholesky FactorizationFactor square Hermitian positive definite matrix into triangular components
LDL Factorization blockLDL FactorizationFactor square Hermitian positive definite matrices into lower, upper, and diagonal components
LU Factorization blockLU FactorizationFactor square matrix into lower and upper triangular components
QR Factorization blockQR FactorizationFactor arbitrary matrix into unitary and upper triangular components
Singular Value Decomposition blockSingular Value DecompositionFactor matrix using singular value decomposition
Backward Substitution blockBackward SubstitutionSolve UX = B for X when U is upper triangular matrix
Cholesky Solver blockCholesky Solver Solve SX = B for X when S is a square Hermitian positive definite matrix
Forward Substitution blockForward SubstitutionSolve LX = B for X when L is lower triangular matrix
LDL Solver blockLDL Solver Solve SX = B when S is square Hermitian positive definite matrix
Levinson-Durbin blockLevinson-DurbinSolve linear system of equations using Levinson-Durbin recursion
LU Solver blockLU Solver Solve AX = B when A is a square matrix
QR Solver blockQR Solver Find minimum-norm-residual solution to AX=B
SVD Solver blockSVD Solver Solve AX = B using singular value decomposition
Cholesky Inverse blockCholesky InverseCompute inverse of Hermitian positive definite matrix using Cholesky factorization
LDL Inverse blockLDL InverseCompute inverse of Hermitian positive definite matrix using LDL factorization
LU Inverse blockLU Inverse使用 LU 分解计算方阵的逆矩阵
Pseudoinverse blockPseudoinverse计算矩阵的摩尔-彭罗斯伪逆

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