Description: 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. Platform: |
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Description: 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. Platform: |
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Description: 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. Platform: |
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Author:Dmitriy |
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Description: 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
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Description: 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. Platform: |
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Author:zineb24 |
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Description: 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. Platform: |
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Author:梁峻超 |
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Description: 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 Platform: |
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Description: 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 Platform: |
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Author:tabce |
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Description: As well as the Jacobi iteration with the Matlab software and gauss-seidel iterative solution of equations Platform: |
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Author:oqbi$742 |
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Description: 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) Platform: |
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Author:NR%25252141788
|
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Description: 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.) Platform: |
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Author:qiuyingyue |
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Search - Jacobi with Gauss-Seidel