搜索资源列表
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
Bmaqr
- qr分解的c语言程序,可以嵌入matlab使用-simulated decomposition of the c language program, can be embedded using Matlab
SVD
- % 奇异值分解 (sigular value decomposition,SVD) 是另一种正交矩阵分解法;SVD是最可靠的分解法, % 但是它比QR 分解法要花上近十倍的计算时间。[U,S,V]=svd(A),其中U和V代表二个相互正交矩阵, % 而S代表一对角矩阵。 和QR分解法相同者, 原矩阵A不必为正方矩阵。 % 使用SVD分解法的用途是解最小平方误差法和数据压缩。用svd分解法解线性方程组,在Quke2中就用这个来计算图形信息,性能相当的好。在计算线性方程组时,一些不能分
householdqr
- 运用househoulder变换求解线性最小二乘问题,实现矩阵的QR分解-Transform househoulder use for solving linear least squares problem, the realization of the QR matrix decomposition
juzhen1
- 矩阵的LU分解、QR分解、Jordan约当标准型.matlab实现-LU decomposition of the matrix, QR decomposition, Jordan Jordan canonical form. Matlab
numericalexercise2
- 这是在VS2010环境下编的.C程序文件,数值分析大作业,北航2015年数值分析A大作业二(幂法、反幂法、QR分解),本人新编的代码比以往版本逻辑更简单更易读。解释清楚,可做C语言新入门者的学习范例-This is in the VS2010 environment compiled C program files. Numerical analysis of the job, the Beijing University of Aeronautics and Astronautics 2015
QR-Schur-decompositi
- QR算法计算一个矩阵的Schur分解。这当然是一个 在特征值的计算中最重要的算法 -QR algorithm to compute the Schur decomposition of a matrix. This is certainly a feature in the calculation of the value of the most important algorithms
Lyapunov_Lorenz
- 基本原理就是首先求解出连续系统微分方程的近似解,然后对系统的Jacobian矩阵进行QR分解,计算Jacobian矩阵特征值的乘积,最后计算出LE和分数维-The basic principle is to first find the approximate solution of differential equations continuous system, then the system will be on the Jacobian matrix QR decomposition p
pinve_svd_qr
- calcul psodo inverse , svd decomposition , QR decomposition , matlab codes
matrix_factorization
- 实现矩阵的各种分解,LU分解,QR分解,Householder分解,Givens 分解-To achieve a variety of matrix decomposition, LU decomposition, QR decomposition, Householder decomposition, Givens decomposition
qr1
- Householder变换进行矩阵的QR分解-Householder transform matrix QR decomposition
house
- 利用householder变换对矩阵做QR分解,它将矩阵分解成一个正规正交矩阵Q与上三角形矩阵R。 - The matrix is decomposed into a regular orthogonal matrix Q and an upper triangular matrix R by QR decomposition using the householder transform.
QR_Decomposition
- 使用格莱姆施密特方法的QR分解程序,附带函数拟合以及图像-Graeme Schmidt method using QR decomposition process
LSQR
- 最小平方QR分解法(LSQR)的C++源码,可以用来学习lsqr-Least squares QR decomposition method (LSQR) of the C++ source code can be used to learn lsqr
reck_caculate
- 一个简单的矩阵运算器,加,减,乘,求逆 性能较好 十字链表存储 QR分解法 稀疏矩阵-A simple matrix calculator, addition, subtraction, multiplication, inverse orthogonal list storage better performance sparse matrix QR decomposition
house
- householder decomposition with column pivoting
QRD_MQAM
- 使用K-BEST树型搜索算法和QR分解,检测信号(Detection of signals using the K-BEST tree search algorithm and QR decomposition)
计算方法
- 吉文斯QR分解,豪斯霍尔德QR分解,三值样条插值法,共轭梯度法,4阶R-K分解(Givens QR decomposition, Moorhouse Holder QR decomposition, three value spline interpolation, conjugate gradient method, 4 order R-K decomposition)
数值分析2
- 使用带双步位移的QR分解法求一个10*10矩阵的特征值(Using the QR decomposition method with two step displacement to obtain the eigenvalues of a 10*10 matrix)
基于 QR 码的自适应抗打印扫描水印算法
- 提出一种基于 QR 码的自适应抗打印扫描盲水印算法。方法 首先对载体 QR 码进行三级小 波变换,并对低频部分进行 4×4 分块 Schur 分解,然后利用子块酉矩阵的系数差值的稳定性,将二值 水印信息自适应嵌入到载体 QR 码中,最后对含水印 QR 码打印扫描并提取出水印信息。同时,算法实 现了盲提取。结果 算法能较好抵抗打印扫描攻击,并对高斯噪声、椒盐噪声、斑纹噪声、泊松噪声、 JPEG 压缩等攻击具有较强的鲁棒性。结论 算法具有较强的抗打印扫描性能,可以广泛应用于数字产品 的版权保