Explore MATLAB source code curated for "线性方程组" with clean implementations, documentation, and examples.
These four implementations solve linear equation systems using Gaussian elimination, column pivoting elimination, complete pivoting elimination methods, and Gauss-Jordan elimination for matrix inversion. The programs are developed in MATLAB language and thoroughly tested under MATLAB 6.5 environment.
MATLAB Implementation of Gauss-Seidel Iterative Method for Solving Linear Equation Systems
MATLAB implementation of iterative methods for solving linear equation systems with code optimization techniques
A comprehensive overview of iteration methods for solving linear equations, featuring key algorithms with code implementation insights: rs - Richardson Iteration, crs - Richardson Parameter Iteration, grs - GRS Iteration, jacobi - Jacobi Iteration, gauseidel - Gauss-Seidel Iteration, SOR - Successive Over-Relaxation, SSOR - Symmetric Successive Over-Relaxation, JOR - Jacobi Over-Relaxation, twostep - Two-Step Iteration, fastdown - Steepest Descent, conjgrad - Conjugate Gradient, preconjgrad - Preconditioned Conjugate Gradient, BJ - Block Jacobi, BGS - Block Gauss-Seidel. Each method includes algorithmic characteristics and computational approaches.
MATLAB implementations of numerical algorithms including linear equations, nonlinear equations, least squares fitting, and related computational methods.
Gaussian elimination method for solving linear equation systems, generally suitable for lower-order equations as performance degrades with higher dimensions. Implementation includes forward elimination and back substitution phases.
Mathematical Tool: LU Decomposition Method for Solving Linear Equations - Efficient and Practical Implementation
SparseLab is a MATLAB software package designed to compute sparse solutions to systems of linear equations, specifically targeting underdetermined systems using advanced iterative thresholding algorithms.
Implementation and Analysis of the Generalized Minimal Residual (GMRES) Algorithm for Solving Large Sparse Linear Equations
Implementation of the Conjugate Gradient Method for Solving Inverse Problems with Code-Optimized Descriptions