搜索资源列表
Algebra
- 基本矩阵运算 : + - *, power, transpose, trace, determinant, minor, matrix of minor, cofactor, matrix of cofactor, adjoint, inverse, gauss, gaussjordan, linear transformation, LU decomposition , Gram-Schmidt process, similarity. b) Basic vectors functions :
h12
- C环境下矩阵运算类,包含矩阵的基本操作,另有其范数,均值等特殊函数-C environment matrix category, including the basic matrix operations, otherwise its norm, the mean number of special function
TVL1_HCS_v1
- % May 2010 % This matlab code implements TVL1 based Hybrid Compressive Sensing using LSQR. % Only suitable the small scale data due to the costly storage and computation. % % A - M x N measurement matrix: random sampling alone or hybrid sampling (ran
TwIST_v2
- % demo_l2_l1 - This demo illustrates the TwIST % algorithm in the l2-l1 optimization problem % % xe = arg min 0.5*||A x-y||^2 + tau ||x||_1 % x % % where A is a generic matrix and ||.||_1 is the l1 norm. % After obtaining the solution we implement a
Matrix
- 这是一个自己编制的完整矩阵类，包括矩阵运算、分解、求逆、范数和特征值等，可以做为数值分析的基础类。-This is a complete matrix of their own class preparation, including matrix computation, decomposition, inverse, norm and eigenvalue, etc., can be used as the basis for numerical analysis class.
Mapack_for_NET
- Mapack可用来做矩阵运算 Mapack is a .NET class library for basic linear algebra computations. It supports the following matrix operations and properties: Multiplication, Addition, Subtraction, Determinant, Norm1, Norm2, Frobenius Norm, Infinity Norm, Rank,
poissonfdm
- 用有限差分法来解偏微分方程，采用高斯——赛德尔迭代方法，并用前后两次迭代差的矩阵的无穷范数作为是否停止迭代的依据。-Using finite difference method to solve partial differential equations, using Gauss- Seidel iterative methods, and poor before and after the two iterations of the infinite matrix norm as the b
fanmiefan
- 求矩阵的逆转置，各种范数以及各种条件数的程序-Purchase reversal matrix, as well as a variety of norm condition number of the procedures
chengxu
- 第一章 误差与范数 第二章 非线性方程（组）的数值解法 第三章 解线性方程组的直接方法第四章 解线性方程组的迭代法第五章 矩阵的特征值与特征向量的计算-Chapter norm error and the second chapter of nonlinear equations (Group) Chapter III of the numerical solution of linear equations solution methods of Chapter IV of the direc
single
- 使用奇异值分解来帮助求解最小二乘问题，特别是在方程系数矩阵不满秩的情况下。-SGELSD computes the minimum-norm solution to a real linear least * squares problem: * minimize 2-norm(| b- A*x |) * using the singular value decomposition (SVD) of A. A is an M-by-N * matrix which
work1
- 计算一个501×501带状矩阵的最大特征值、最小特征值、谱范数条件数和行列式值。內附完整的问题描述说明文档。-Calculating a 501 × 501 matrix band maximum eigenvalue, the smallest eigenvalue, spectral norm condition number and determinant values. Included a complete descr iption of the problem.
Matrix-theory
- 矩阵理论课件，系统讲述线性空间与线性变换、内积空间、特殊变换及其矩阵、矩阵的标准型、向量范数和矩阵范数，以及矩阵分解等六章内容。-The Matrix Theory courseware systemticly introduce the linear spaces and linear transformations, inner product spaces, special transformation and its matrix, the matrix Standard, the ve
Matrix_test
- 在vs2010中实现了一个矩阵类主要功能有矩阵间的基本运算，矩阵下标访问，矩阵的LU分解，QR分解，特征值，矩阵的秩，矩阵的范数，以及基于矩阵元素的基本函数运算。-Vs2010 in the matrix between the main function of a matrix class operator matrix subscr ipting matrix LU decomposition, QR decomposition, eigenvalues, the rank of the m
G-S
- 本程序为G-S迭代法，若系数矩阵满足 1.G-S迭代矩阵谱半径小于一 2.jacobi迭代矩阵一范数或无穷范数小于一 3.系数矩阵A正定 4.系数矩阵A严格对角占优或不可约对角占优 则可返回A*x=b的解。算法迭代次数比 x=M*x+g形式的标准化迭代次数多，但所用时间少很多。-The program for the G-S iteration method, if the coefficient matrix 1.G-S iterative matrix spect
Matrix-Norm
- 本课件详细介绍了图像处理中的向量范数和矩阵范数的定义，并给出了相关应用。-The courseware details image processing vector norm and the matrix norm is defined, and gives related applications.
Norm-of-matrix
- 各类矩阵的范数，包含行范数，列范数，以及2范数，有利于解决各种范数问题-Norm of matrix norm, contains the row, column norm, and 2 norm, is conducive to resolving the various norm problem
concept-of-orthogonal
- A matrix nearness problem consists of finding, for an arbitrary matrix A, a nearest member of some given class of matrices, where distance is measured in a matrix norm. A survey of nearness problems is given, with particular emphasis on the fun
matrix-completion-via-threshloding
- Matrix Completion via Iterated Thresholding min nuclear-norm(X) subject to ||y - M(X)||_2<e-Matrix Completion via Iterated Thresholding min nuclear-norm(X) subject to ||y- M(X)||_2<err
Parafac codes
- PARAFAC源程序，可以用于平行因子分析处理的算法，很全很好用(unction [A,B,C,LLF,I,J,K] = parafac(XPK,I,N,epsilon) % PARAFAC Parallel factor analysis for an three-way data array % The iterative process is continued until that m > 300 or ABS((LF(m)-LF(m-1)) % /LF(m-1)) is l
（强化学习入门）David Silver
- 深度学习的中文版本，里面详细介绍了深度学习的各种算法，其中还有一些用到的基础内容，例如矩阵和向量的范数(Chinese version of the depth of learning, which detailed the depth of learning algorithms, some of which used the basics, such as vector and matrix norm)