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Inplementation of Gauss-Jacobi method
Update : 2025-02-19 Size : 30kb Publisher : Jaziel

DL : 0
(1)用Doolittle三角分解(LU)法解方程组。 (2)分别用Jacobi迭代, Gauss-Seidel迭代法解方程组。 -(1) Triangle Doolittle decomposition (LU) Solving equations. (2), respectively, with Jacobi iteration, Gauss-Seidel iteration method for solution of equations.
Update : 2025-02-19 Size : 2kb Publisher : 娜娜

DL : 0
In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method. Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is guaranteed if the matrix is either diagonally dominant, or symmetric and positive definite.
Update : 2025-02-19 Size : 106kb Publisher : John

DL : 0
In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method. Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is only guaranteed if the matrix is either diagonally dominant, or symmetric and positive definite.
Update : 2025-02-19 Size : 3kb Publisher : ismaail

In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method. Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is only guaranteed if the matrix is either diagonally dominant, or symmetric and positive definite.
Update : 2025-02-19 Size : 51kb Publisher : Dmitriy

Chapter 3. The Solution of Linear Systems AX = B Algorithm 3.1 Back Substitution Algorithm 3.2 Upper-Triangularization Followed by Back Substitution Algorithm 3.3 PA = LU Factorization with Pivoting Algorithm 3.4 Jacobi Iteration Algorithm 3.5 Gauss-Seidel Iteration-Chapter 3. The Solution of Linear Systems AX = B Algorithm 3.1 Back Substitution Algorithm 3.2 Upper-Triangularization Followed by Back Substitution Algorithm 3.3 PA = LU Factorization with Pivoting Algorithm 3.4 Jacobi Iteration Algorithm 3.5 Gauss-Seidel Iteration
Update : 2025-02-19 Size : 19kb Publisher : Paola de Oliveira

DL : 0
this Laplace 2D . i solve with Jacobi Iteration method ,Point Gauss-seidel Interation method,Line Gauss-Seidel Iteration method ,Point Successive Over-Relaxation method (PSOR),Line Successive Over-Relaxation method (LSOR)-this is Laplace 2D . i solve with Jacobi Iteration method ,Point Gauss-seidel Interation method,Line Gauss-Seidel Iteration method ,Point Successive Over-Relaxation method (PSOR),Line Successive Over-Relaxation method (LSOR)
Update : 2025-02-19 Size : 1kb Publisher : Thanh

用Jacobi Gauss-seidel SOR迭代法求解线性方程组-With Jacobi Gauss-seidel SOR iterative method for solving linear equations
Update : 2025-02-19 Size : 49kb Publisher : 李春兰

In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method. Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is only guaranteed if the matrix is either diagonally dominant, or symmetric and positive definite. It was only mentioned in a private letter from Gauss to his student Gerling in 1823.[1] A publication was not delivered before 1874 by Seidel.
Update : 2025-02-19 Size : 7kb Publisher : zineb24

一种非线性代数方程组的迭代解法。最早用于解算电力系统潮流。这种方法具有程序编制简单、占用内存少的优点,但算法收敛性差,计算时间长。-In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method. Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is only guaranteed if the matrix is either diagonally dominant, or symmetric and positive definite. It was only mentioned in a private letter Gauss to his student Gerling in 1823.[1] A publication was not delivered before 1874 by Seidel.
Update : 2025-02-19 Size : 1kb Publisher : 梁峻超

DL : 0
数值方法解线性方程组,包括雅克比迭代法,高斯赛德尔迭代法和SOR超松弛迭代法的例程。-Linear equations with Jacobi, Gauss-Seidel method and SOR iteration.
Update : 2025-02-19 Size : 169kb Publisher : hzf

结合java图形界面编程实现了计算方法中的相关的算法,包含:雅可比迭代 高斯-塞德尔迭代 拉格朗日插值 主元素高斯消去 高斯-约当消去 牛顿插值 不含列主元高斯约当法 二次多项式拟合 一次多项式拟合 二分法 牛顿迭代 三次样条插值 三对角的追赶法-Combined with java GUI programming calculation method of the related algorithms, comprising: Jacobi iteration Gauss- Seidel iterative Lagrange Interpolation main elements of Gaussian elimination Gauss- Jordan elimination Newton interpolation excluding out PCA Gauss Jordan Method quadratic polynomial fitting a polynomial fitting dichotomy of Newton iteration cubic spline interpolation method Tridiagonal catch
Update : 2025-02-19 Size : 6kb Publisher : 李力

In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method. Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is only guaranteed if the matrix is either diagonally dominant, or symmetric and positive definite. It was only mentioned in a private letter Gauss to his student Gerling in 1823.[1] A publication was not delivered before 1874 by Seidel-In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method. Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is only guaranteed if the matrix is either diagonally dominant, or symmetric and positive definite. It was only mentioned in a private letter Gauss to his student Gerling in 1823.[1] A publication was not delivered before 1874 by Seidel
Update : 2025-02-19 Size : 1kb Publisher : Zolo

用Matlab软件以及雅克比迭代和高斯-赛德尔迭代解方程组-As well as the Jacobi iteration with the Matlab software and gauss-seidel iterative solution of equations
Update : 2025-02-19 Size : 16kb Publisher : tabce

As well as the Jacobi iteration with the Matlab software and gauss-seidel iterative solution of equations
Update : 2025-02-19 Size : 16kb Publisher : oqbi$742

用Matlab软件以及雅克比迭代和高斯-赛德尔迭代解方程组(As well as the Jacobi iteration with the Matlab software and gauss-seidel iterative solution of equations)
Update : 2025-02-19 Size : 16kb Publisher : NR%25252141788

浙大PTA练习系统NA1004 比较雅各比迭代和高斯塞德尔迭代(Use Jacobi and Gauss-Seidel methods to solve a given n×n linear system A x ⃗ = b ⃗ with an initial approximation x ⃗ (0) . Note: When checking each a ii , first scan downward for the entry with maximum absolute value (a ii included). If that entry is non-zero, swap it to the diagonal. Otherwise if that entry is zero, scan upward for the entry with maximum absolute value. If that entry is non-zero, then add that row to the i-th row.)
Update : 2025-02-19 Size : 108kb Publisher : qiuyingyue
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