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KLU-1.1.0.tar
- 对稀疏矩阵进行LU分解,可用于电路仿真、FEM求解等 C语言-KLU is a sparse LU factorization algorithm well-suited for use in circuit simulation. KLU is a sparse LU factorization algorithm well-suited for use in circuit simulation. It was highlighted in the May 2007 issue of SIA
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
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
sparseBSS1
- 稀疏分量分解。 function [y A]=sparseBSS1(X,L,langda,G,h,delta)-function [y A]=sparseBSS1(X,L,langda,G,h,delta) ---------------------------------------------------------------- 2009-04-15 YangZhicong X: observed signal,each ro
nmfsc
- 稀疏约束的非负矩阵分解Non-negative Matrix Factorization with Sparseness Constraints-Non-negative Matrix Factorization with Sparseness Constraints
sparse-decomposition
- 基于稀疏表示的卡通纹理分解程序,能完成卡通纹理的分解-The program can complete that texture based on sparse decomposition process that cartoon, cartoon texture to complete the decomposition.
SPARSE-AND-LOW-RANK
- 稀疏和低秩矩阵分解。 This paper focuses on the algorithmic improvement for the sparse and low-rank recovery.- Sparse and Low-Rank Matrix Decomposition Via Alternating Direction Methods.The problem of recovering the sparse and low-rank components of a matrix
MATLAB-Numerical-Evaluation
- Matlab 数值计算讲义和例程,包括如下章节: 范数、条件数和方程解的精度 矩阵特征值和矩阵函数 奇异值分解 函数的数值导数和切平面 函数极值点 数值积分 随机数据的统计描述 多项式拟合和非线性最小二乘 插值和样条 Fourier分析 常微分方程 稀疏矩阵-Matlab numerical evaluation
sichashu
- 选择使用matlab对图像进行四叉树分解,并且显示稀疏矩阵的结果。-Choose to use the matlab quadtree decomposition of the image, and sparse matrix results.
KSVD_Matlab_ToolBox
- 稀疏编码,去噪,奇异值分解 MATLAB-Sparse coding, denoising, singular value decomposition MATLAB
sichashufenjie
- 对示例图像进行四叉树分解,并以图像的形式显示所得的稀疏矩阵,同时取得所有子块和符合各种维度条件的子块数目。-Quadtree decomposition of the sample images, and the form of images obtained sparse matrix, at the same time to obtain the number of sub-blocks of all sub-blocks and meet the conditions of the var
C-Program-examples
- 河内塔 费式数列 巴斯卡三角形 三色棋 老鼠走迷官(一) 老鼠走迷官(二) 骑士走棋盘 八个皇后 八枚银币 生命游戏 字串核对 双色、三色河内塔 背包问题(Knapsack Problem) 数、运算 蒙地卡罗法求 PI Eratosthenes筛选求质数 超长整数运算(大数运算) 长 PI 最大公因数、最小公倍数、因式分解 完美数 阿姆斯壮数 最大访客数 中序式转
sinccompleteCi
- 程序源码简单易懂实现了对稀疏矩阵进行incomplete Cholesky分解的功能,具有一定参考价值。 -Easy to understand program source code to achieve the incomplete Cholesky decomposition of sparse matrices, with a certain reference value.
RASL-Robust-Alignment
- 此篇论文是利用稀疏低秩矩阵分解来实验的鲁棒图片的矫正。-This paper is the use of sparse low rank matrix decomposition to experimental robust image correction。
SVDLIBC-win
- SVDLIBC是一个使用Lanczos算法计算稀疏矩阵SVD(奇异值分解)的C语言函数库,原本在只能Linux下编译,这个版本是对其进行修改后的windows版本,可以在VC++或MinGW下使用。-SVDLIBC is a C library computing the SVD(Singular Value Decomposition) of a sparse matrix using the Lanczos Algorithm. Originally, it can only compile
ldu
- 将一个稀疏矩阵分解因子,构成上三角矩阵,对角矩阵和下三角矩阵相乘的形式。即LDU分解。-Factoring a sparse matrix, constitute the upper triangular matrix, in the form of a diagonal matrix and lower triangular matrix multiplication. That LDU decomposition.
matrix_lu1
- 稀疏矩阵分解,LU分解,快速高效的分解矩阵-Sparse matrix factorization, LU decomposition, fast and efficient decomposition of the matrix
Curvelet
- 曲波变换是图像处理领域中稀疏表示最常用的一种字典,其中MCA分解模型中经常用到。-Bo transform the field of image processing is the most common kind of sparse representation dictionary MCA decomposition model which is often used.
focuss
- focuss算法 关于图像稀疏性分解中字典学习的经典算法-focuss on the image sparse decomposition algorithm in the classical dictionary learning algorithms
sparse-frequency-decomposition
- 包括TVD去噪(速度非常快),最小平方最优程序,用于稀疏频率分解,很好用。-Including TVD noising (very fast), the least-squares best program for sparse frequency resolution, very good use.