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Description: 全主元高斯－约当消去法，解线性方程组，内含函数以及调用例子-all PCA Gauss-Jordan elimination method, the solution of linear equations, functions and includes examples Call
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Description: 数值分析算法描述与习题解答，由清华大学徐士良教书，用C编写的各种数学算法。比如：托伯利兹型线性代数方程组的递推算法，全选主元高斯消去法解复系数线形代数方程组，复矩阵求逆的全选主元高斯-约当法，等；-numerical analysis algorithm description and answer the questions from Qinghua University XU Shi-liang, teaching C prepared by the various mathematical algorithms. For example : Toeplitz linear algebraic equations, a recursive algorithm, the whole election PCA Gaussian Elimination demultiplexing coefficient of linear algebraic equations, matrix inversion of the entire election PCA Gaussian-about when the law;
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Description: 高斯约当消元法解线性方程组,附源代码.
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Description: 全主元高斯－约当消去法，解线性方程组，内含函数以及调用例子-all PCA Gauss-Jordan elimination method, the solution of linear equations, functions and includes examples Call
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Description: 数值分析算法描述与习题解答，由清华大学徐士良教书，用C编写的各种数学算法。比如：托伯利兹型线性代数方程组的递推算法，全选主元高斯消去法解复系数线形代数方程组，复矩阵求逆的全选主元高斯-约当法，等；-numerical analysis algorithm description and answer the questions from Qinghua University XU Shi-liang, teaching C prepared by the various mathematical algorithms. For example : Toeplitz linear algebraic equations, a recursive algorithm, the whole election PCA Gaussian Elimination demultiplexing coefficient of linear algebraic equations, matrix inversion of the entire election PCA Gaussian-about when the law;
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Description: 全主元高斯约当消去法
2.LU分解法
3.追赶法
4.五对角线性方程组解法
5.线性方程组解的迭代改善
6.范德蒙方程组解法
7.托伯利兹方程组解法
8.奇异值分解
9.线性方程组的共轭梯度法
10.对称方程组的乔列斯基分解法
11.矩阵的QR分解
12.松弛迭代法-PCA-wide Gauss Jordan elimination method 2.LU decomposition method 3. To catch up with law 4. Five linear equations solution 5. Linear equations of the iterative improvement of solution 6. Vandermonde equations Solution 7.托伯利兹Solution of equations 8. Singular Value Decomposition 9. linear equations of the conjugate gradient method 10.乔列斯基symmetric linear decomposition method 11. matrix QR decomposition 12. relaxation iteration method
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Description: 本书目录列表：
第1章线性代数方程组的解法
1.全主元高斯约当消去法
2.LU分解法
3.追赶法
4.五对角线性方程组解法
5.线性方程组解的迭代改善
-Directory listing of this book: Chapter 1 of the solution of linear algebraic equations 1. The whole PCA Gauss Jordan elimination 2.LU decomposition 3. To catch up with France 4. 5 diagonal of linear equations 5. Linear equations Iterative Solutions to improve the
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Author: luoshong1 |
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Description: 采用全选主元高斯－约当消去法求解复系数线性代数方程组。其中ar存放复系数矩阵实部，ai存放复系数矩阵虚部。br存放右端复常数向量实部，返回解向量实部；bi存放右端复常数向量虚部，返回解向量虚部。-With full pivoting Gauss- Jordan elimination method for solving linear algebraic equations with complex coefficients. Which ar stored real part of complex coefficient matrix, ai imaginary part of coefficient matrix storage complex. br right end storage complex real constant vector, returns solution vectors of real bi kept constant vector imaginary part of the right end of rehabilitation, return solution vector imaginary.
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Author: Shepard |
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Description: C#实现的基本数值算法：利用高斯消元法求线性方程组的解、利用约当消元法求线性方程组的解、一元非线性方程实根的数值算法及程序实现-C# implementation of basic numerical algorithms: Gaussian elimination method of solution of linear equations using Jordan Elimination Method of linear equations, one dollar real roots of nonlinear equations Numerical Algorithm and Program
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Author: 曾文斌 |
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Description: 提出了一种求解电磁场有限元 边界元混合法所生成的线性方程组的有效方法 ———内观
法结合多波前法.由于该线性方程组的系数是一个部分稀疏部分满填充的矩阵,为了加速求解,应用内观法将系数矩阵分为 2块,一块是有限元法形成的稀疏矩阵,另一块是边界元法生成的满阵,然后用多波前法求解稀疏矩阵方程,用高斯 约当消去法解满阵方程. 采用该方法,计算了二维多层介质柱体的雷达散射截面.计算结果表明,该方法的计算效率远远高于传统的高斯法.-Proposed for solving mixed finite element boundary element linear equations generated by an effective method of Vipassana--- a combination of multi wave front method. Since the coefficients of linear equations is a part of the sparsely populated part of the full matrix, in order to speed up the solution, application of Vipassana coefficient matrix is divided into two, one is the finite element method for the formation of the sparse matrix, the other is the boundary element method generates the full array, and then use the multifrontal method for solving sparse matrix equation Gauss Jordan elimination method with full matrix equation solution. use this method to calculate the two-dimensional multi-layer dielectric cylinder of the radar cross section. The results show the computational efficiency of this method is much higher than the traditional Gaussian law.
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Description: 大型稀疏方程组的全选主元高斯-约当消去法，面对迭代法解线性方程组是会出现除数为0的情况，可用这种方法解决。-the face of iterative method for solving linear equations is zero divisor will be the case, can be resolved in this way.
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Author: 李宁 |
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Description: 第1章线性代数方程组的解法
1.全主元高斯约当消去法
2.LU分解法
3.追赶法
4.五对角线性方程组解法
5.线性方程组解的迭代改善
6.范德蒙方程组解法
7.托伯利兹方程组解法
-Chapter 1, the solution of linear algebraic equations
1 full pivot Gauss Jordan elimination
2.LU decomposition
3 catch-up method
4 five diagonal linear equations solution
5 Iterative solution of linear equations to improve
6 Solution of Vandermonde equations
7. Tuobo Leeds solution of equations
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Author: dean1689 |
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Description: 全选主元高斯-约当消去法同时求解系数矩阵相同而右端具有m组常数向量的线性代数方程组AX=B的全部解-QuanXuan primary gaussian-about when elimination technique and then the coefficient matrix is the same and the right side of the constant vector with m linear algebra equations AX = B of all solutions
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Author: 戴敏 |
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Description: 可实现的算法：软件说明：
1.全主元高斯约当消去法2.LU分解法3.追赶法4.五对角线性方程组解法5.线性方程组解的迭代改善6.范德蒙方程组解法7.托伯利兹方程组解法8.奇异值分解9.线性方程组的共轭梯度法10.对称方程组的乔列斯基分解法11.矩阵的QR分解12.松弛迭代法第2章插值1.拉格朗日插值2.有理函数插值3.三次样条插值4.有序表的检索法5.插值多项式6.二元拉格朗日插值-The algorithm can be realized: Software Description: a full principal component Gauss Jordan elimination 2.LU decomposition method 3 to catch up with France. Five linear equations solution. Linear equations iterative improvement of 6. Vandermonde Equations for 7. Tuobo Leeds equations solution. singular value decomposition of linear equations of the conjugate gradient method 10. the Cholesky decomposition method for symmetric linear matrix of QR decomposition. relaxation iterative method Chapter 2 interpolation Lagrange interpolation. rational function interpolation. retrieval method of cubic spline interpolation. ordered table 5. interpolation polynomial 6 dual Lagrange interpolation
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Author: liuwei |
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Description: 用高斯--约当列主元消去法求线性方程组的解-Gauss- Jordan elimination method for main-element solution of linear equations
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Author: 黄磊 |
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Description: 全选主元高斯-约当消去法求解稀疏线性方程组
输入参数a[]系数矩阵，n线性方程阶数，b[]右端项
输出参数b[]方程组的解
返回值 ： 1求解成功 0求解失败-Select the main element Gauss- Jordan elimination method for solving sparse linear equations
Input parameters a [] coefficient matrix, n order linear equations, b [] right-hand side
Output parameter b solution of equations []
Returns: 1 0 Solving failure to solve success
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Author: 李欣 |
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