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TherealizationofParallelLUfactorizationbasedonFPGA
- 本文首先介绍了稀疏矩阵的特点和研究稀疏矩阵分解的意义，接着讨论了稀疏矩阵各种快速算法并给出了本文所采用的方法。在此基础上详细说明了稀疏矩阵模拟排序算法，直接LU分解算法，符号LU分解算法，数值LU分解算法及这些算法在FPGA上的实现过程。最后为充分发挥FPGA作为一种可编程逻辑器件的优势，将单核数值LU分解扩展为多核并行LU分解结构，并使用BDB矩阵对该结构进行了验证，给出并分析了实验结果。-Firstly,the characteristies and research value of sp
CGandLU
- compare CG iterations and LU factorization when solving linear equation A*X=b
LU
- 利用高斯消元列选主元法进行矩阵的LU分解和利用此分解解线性方程组-LU matrix factorization and use this decomposition of Linear Equations
smartinv
- 通过求解LU分解解线性方程组 大型稀疏矩阵LU分解有用的是容易计算的。不是最快的方式来计算逆矩阵，但要避免消耗储存的问题-computing selected entries of the inverse, by solving a sequence of linear equations after doing an LU factorization. Useful for large sparse matrix which LU decomposition is easy to c
LU_factor.m
- Method with Gaussian Elimination without Pivoting LU factorization of matrix A using Gaussian-elimination without pivoting Inputs : A --> n x n matrix Outputs : L (lower triangular) && U (upper triangular) - Method with Gaussi
linearsystem
- 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 Al
LU_DecomME1
- MATLAB 数值分析，矩阵分解实例，LU分解-MATLAB numerical analysis, matrix factorization example, LU decomposition
matrix
- 此包包含了众多矩阵处理程序，能够满足矩阵处理的一般要求，由于将各功能分开到不同的“.cpp”文件中，故使用时需要用户自行选取更换合适自己使用的“.cpp”文件。其中，矩阵功能有：输出矩阵、矩阵转置、矩阵归一化、判断矩阵对称、判断矩阵对称正定、全选主元法求矩阵行列式、全选主元高斯(Gauss)消去法求一般矩阵的秩、用全选主元高斯-约当(Gauss-Jordan)消去法计算实(复)矩阵的逆矩阵、用“变量循环重新编号法”法求对称正定矩阵逆、特兰持(Trench)法求托伯利兹(Toeplitz)矩阵逆、
Matrix-factorization-C-program
- 矩阵分解的C程序 包括有矩阵的LU分解，矩阵的UU分解还有共轭梯度法-Matrix decomposition of the C program, including a matrix LU decomposition, the UU decomposition of the matrix conjugate gradient method
main
- 矩阵的LU分解的实现,用户输入增广矩阵后,会自动输出L型矩阵和U型矩阵-Matrix LU factorization, implementation, user input augmented matrix, it will automatically output the L-type matrix and the U-matrix
Gauss
- 线性方程组的数值解法的Matlab代码 采用Gauss算法和LU分解-Matlab code of the numerical solution of linear equations using Gauss algorithm and LU factorization
tridiagLU.m
- LU factorization of tridiagonal matrix
resolution_Lu
- In linear algebra, LU decomposition (where LU stands for Lower Upper , and also called LU factorization) factors a matrix as the product of a lower triangular matrix and an upper triangular matrix. The product sometimes includes a permutation matrix
LU_FACTORIZATION
- 使用MATLAB实现矩阵的LU分解，MATLAB自带的函数是无法实现计算方法中的LU分解的；-MATLAB LU FACTORIZATION
hw1_PC_NB
- LU Factorization of matrix using OpenMP
DirectMethodsLinearSystems
- 解线性方程组方法：（1）Gauss消去法 (2)杜立特尔直接三角分解法 （2）追赶法解三对角方程 平方根分解法解对称矩阵 的MATLAB源代码-the matlab source codes of Direct Methods for Solving Linear Systems:(1)Gaussian Elimination (2)LU Factorization(Doolittle Method) (3)Pursue Method for Diagonally Dominant Matric
resolution_gauss_descents
- In numerical analysis, LU decomposition (where LU stands for Lower Upper , and also called LU factorization) factors a matrix as the product of a lower triangular matrix and an upper triangular matrix. The product sometimes includes a permutation mat
code3
- splu Square PA=LU factorization *with row exchanges*.-splu Square PA=LU factorization *with row exchanges*.
matlab
- LINEAR SYSTEMS AND GAUSSIAN ELIMINATION THE LU FACTORIZATION Gauss-Seidel iteration SOR (successive over-relaxation) iteration
invert_ij
- LU Factorization to take the inverse