MATLAB 中的定点矩阵运算
R2026b使用这些函数执行定点矩阵运算并生成高效的 C/C++ 代码。这些函数使用对嵌入式设备高效的基于 CORDIC 的算法求解线性方程组并执行核心矩阵运算，如 QR 分解和奇异值分解。使用包含的 Fixed-Point Designer™ 函数以解析方式确定线性系统求解器和矩阵分解模块的最佳定点数据类型。
有关这些算法的 Simulink® 模块实现，请参阅Simulink 中的定点矩阵运算。有关 MATLAB® 和 Simulink 中数学运算的基于 CORDIC 和其他嵌入式高效实现，请参阅MATLAB 和 Simulink 中的定点数学运算。
函数
主题
- Determine Fixed-Point Types for QR Decomposition
Use
fixed.qrFixedpointTypesto determine fixed-point types for computation of QR decomposition. - Determine Fixed-Point Types for Q-less QR Decomposition
Use
fixed.qlessqrFixedpointTypesto determine fixed-point types for computation of Q-less QR decomposition. - Algorithms to Determine Fixed-Point Types for Complex Q-less QR Matrix Solve A'AX=B
Derivation of algorithms for determining fixed-point types for complex Q-less QR matrix solve.
- Determine Fixed-Point Types for Complex Q-less QR Matrix Solve A'AX=B
Use
fixed.complexQlessQRFixedpointTypesto determine fixed-point types for computation of the complex least-squares matrix equation. - Determine Fixed-Point Types for Complex Q-less QR Matrix Solve with Tikhonov Regularization
This example shows how to use the
fixed.complexQlessQRMatrixSolveFixedpointTypesfunction to analytically determine fixed-point types for the solution of the complex least-squares matrix equation - Algorithms to Determine Fixed-Point Types for Complex Least-Squares Matrix Solve AX=B
Derivation of algorithms for determining fixed-point types for complex QR matrix solve.
- Determine Fixed-Point Types for Complex Least-Squares Matrix Solve AX=B
Use
fixed.complexQRFixedpointTypesto determine fixed-point types for computation of the complex least-squares matrix equation. - Determine Fixed-Point Types for Complex Least-Squares Matrix Solve with Tikhonov Regularization
This example shows how to use the
fixed.complexQRMatrixSolveFixedpointTypesfunction to analytically determine fixed-point types for the solution of the complex least-squares matrix equation - Algorithms to Determine Fixed-Point Types for Real Q-less QR Matrix Solve A'AX=B
Derivation of algorithms for determining fixed-point types for real Q-less QR matrix solve.
- Determine Fixed-Point Types for Real Q-less QR Matrix Solve A'AX=B
Use
fixed.realQlessQRFixedpointTypesto determine fixed-point types for computation of the real least-squares matrix equation. - Determine Fixed-Point Types for Real Q-less QR Matrix Solve with Tikhonov Regularization
This example shows how to use the
fixed.realQlessQRMatrixSolveFixedpointTypesfunction to analytically determine fixed-point types for the solution of the real least-squares matrix equation - Algorithms to Determine Fixed-Point Types for Real Least-Squares Matrix Solve AX=B
Derivation of algorithms for determining fixed-point types for real least-squares matrix solve.
- Determine Fixed-Point Types for Real Least-Squares Matrix Solve AX=B
Use
fixed.realQRMatrixSolveFixedpointTypesto determine fixed-point types for computation of the real least-squares matrix equation. - Determine Fixed-Point Types for Real Least-Squares Matrix Solve with Tikhonov Regularization
This example shows how to use the
fixed.realQRMatrixSolveFixedpointTypesfunction to analytically determine fixed-point types for the solution of the real least-squares matrix equation - Compute Forgetting Factor Required for Streaming Input Data
Use
fixed.forgettingFactorandfixed.forgettingFactorInverseto compute forgetting factor. - Estimate Standard Deviation of Quantization Noise of Complex-Valued Signal
Use
fixed.complexQuantizationNoiseStandardDeviationto estimate standard deviation of quantization noise. - Estimate Standard Deviation of Quantization Noise of Real-Valued Signal
Use
fixed.realQuantizationNoiseStandardDeviationto estimate standard deviation of quantization noise.
精选示例
Perform QR Factorization Using CORDIC
Write MATLAB code that works for both floating-point and fixed-point data types. The algorithm used in this example is the QR factorization implemented via CORDIC.
