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Multiscale~wedgelet~imageanalysis~fast~decompositi
- in this paper,we show that an efficient multiscale wedgelet decomposition is possible if we carefully choose the set of possible wedgelet orientations.-in this paper. we show that an efficient Aperture wedgelet d ecompos
Multiscale~wedgelet~imageanalysis~fast~decompositi
- in this paper,we show that an efficient multiscale wedgelet decomposition is possible if we carefully choose the set of possible wedgelet orientations.-in this paper. we show that an efficient Aperture wedgelet d ecompos
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
hht2002
- 黄变换的代码，经验模式分解，可用于信号分解-Huang transform the code, empirical mode decomposition can be used for signal decomposition
cholesky
- 用matlab编写的cholesky分解程序，希望对大家有些帮助-Matlab prepared using Cholesky decomposition procedures, in the hope that some U.S. help
sparse_decomposition
- 基于遗传算法改进的稀疏分解算法，已调试过了，写论文是编写的-Based on genetic algorithm to improve the sparse decomposition algorithm, has been testing and writing papers are prepared
wavemarksvd
- 利用svd的一种水印方法。SVD即奇异值分解(Singular Value Decomposition)算法。 -A watermarking method using svd. Singular value decomposition SVD that (Singular Value Decomposition) algorithm.
Benders_Decomposition
- 一个好的最短路径算法参考文献——A benders decomposition approach-A benders decomposition approach for the robust shortest path problem with interval data.
gussl
- 掌握用MATLAB编写LU分解法与PLU分解法的程序；-The preparation of master LU decomposition method with MATLAB and the PLU decomposition procedure
Alg_LU
- the LU decomposition is a matrix decomposition which writes a matrix as the product of a lower triangular matrix and an upper triangular matrix.
Real-matrix-decompositi
- 利用Householder变换及变换QR算法对一般实矩阵进行奇异值分解。-Real matrix singular value decomposition of general procedures
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