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lab2答案
- 设计一个因子分解算法，并分析其复杂性。用你熟悉的计算机语言实现以上算法，记录3个测试结果。-design a factorization algorithm and analysis of their complexity. You familiar with the computer language achieve the above algorithm, recorded three test results.
lsq
- The module LSQ is for unconstrained linear least-squares fitting. It is based upon Applied Statistics algorithm AS 274 (see comments at the start of the module). A planar-rotation algorithm is used to update the QR- factorization. This makes it
slu_dist.ps
- 稀疏矩阵分解的最好方法之一，LU分解，快速高效的分解矩阵-sparse matrix factorization one of the best ways, LU decomposition, fast and efficient decomposition matrix
PolynomialIncludingAllFunctions
- 一元多项式符号计算-含因式分解版 不仅包含+,-,*,/,多项式求值,数值积微分,(内含多项式求根子程序),定与不定积分,还有因式分解(求根法). 用单链表.输入格式按提示.-one yuan polynomial symbolic computation-containing factorization version not only contains ,-,*,/, polynomial evaluation, Numerical plot differential (intron
connvert
- 对矩阵进行LU分解并求逆，该程序适用于任意维数方阵，-right matrix factorization and inverse, the procedures applicable to arbitrary dimension arrays
cholesky323232
- 平均因子分解法，适用于正定矩阵First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square matrix X, the Cholesky decomposition of X is the factorization X=U U, where U is the square root matrix of X, and satisfies:
LU_decompostion
- 矩阵的LU分解的改进型算法。优点是快捷-matrix factorization of the improved algorithm. Advantage is speed.
t2_3
- 本题采用的计算方法为：矩阵的 分解和Cholesky分解。根据Gauss消去法的的矩阵意义，可以将矩阵A分解为一个单位下三角矩阵与一个上三角矩阵的乘积即：即矩阵的LU分解A=LU，进而可以分解为： 的形式。当A为对称矩阵时，A可分解为： 的形式。-that the use of the method of calculating : matrix decomposition and Cholesky decomposition. According to the Gauss eliminatio
cad01
- 用LU分解实现解方程，用visual C++编写，可以使用一下-with factorization of solving equations, using visual C, can use this to s
nmf
- Code to run the Non-negative Matrix Factorization algorithm as presented in the Lee, Seung 1999 Nature paper.
power2
- 2． Using QR factorization to find all of the eigenvalues and eigenvectors for the following matrix
GEE
- The "GEE! It s Simple" package illustrates Gaussian elimination with partial pivoting, which produces a factorization of P*A into the product L*U where P is a permutation matrix, and L and U are lower and upper triangular, respectively. The fu
ldiv
- The "GEE! It s Simple" package illustrates Gaussian elimination with partial pivoting, which produces a factorization of P*A into the product L*U where P is a permutation matrix, and L and U are lower and upper triangular, respectively. The fu
3107002005_2nd_A_LDL
- LDL分解。作为矩阵方程数值解法最基础的矩阵分解算法，LDL算法可以高效分解对称矩阵。-LDL decomposition. Numerical Solution of matrix equation as the most basic matrix factorization algorithm, LDL decomposition algorithm can be efficient symmetric matrix.
numerical-method
- 数值方法课程中的程序，如GaussSeidel迭代法解方程组，Jacobi迭代法解方程组，SOR迭代法解方程组，杜利特尔矩阵分解以及矩阵的直接解法，拉格朗日插值等11个程序。-Courses in numerical methods, such as iterative method for solution GaussSeidel equations, Jacobi iterative method for solution of equations, SOR iterative method
FHSVD
- HankelToeplitz and Takagi Factorization Package
Gram_S
- classical Gram-Schmidt(unstable) (reduced QR factorization).A:m-by-n matrix. (m>=n)Q:m-by-n unitary matrix.R:n-by-n upper triangular.-classical Gram-Schmidt(unstable) (reduced QR factorization).A:m-by-n matrix. (m>=n)Q:m-by-n unitary matrix.R:
factorization
- 对整数进行因数分解，输入整数，输出因数分解-Factorization of the integers
factorization
- factorization prime digit
Positive-integer-factorization
- 实现正整数分解功能，能够分解任意给定的非零整数-Positive integer factorization, can decompose any given non-zero integer