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LAPACK-3.4.1.tar
- LAPACK，其名為Linear Algebra PACKage的縮寫，是一以Fortran程式語言寫就，用於數值計算的函式集。 LAPACK提供了豐富的工具函式，可用於諸如解多元線性方程式、線性系統方程組的最小平方解、計算特徵向量、用於計算矩陣QR分解的Householder轉換、以及奇異值分解等問題。-LAPACK (Linear Algebra PACKage) is a software library for numerical linear algebra. It provides
fanmifa
- 反幂法计算最小特征值及其特征向量，matlab调用函数-Inverse power method to calculate the smallest eigenvalue and its eigenvectors matlab function is called
rpmethod
- 矩阵的特征值计算程序，包括整个流程的具体计算，每一步骤都很详细-Matrix eigenvalue calculation procedures, including the entire process of specific, very detailed each step
Power-law
- 数值分析中，用幂法和反幂法去计算矩阵的最小特征值和最大特征值-Numerical analysis, using the power method and inverse power method to calculate the minimum eigenvalue of the matrix and the largest eigenvalue
wenli
- MATLAB14个特征值的提取程序，包括能量、熵、对比度、相关性、逆差等14个特征值的程序。-MATLAB14 eigenvalue extraction program, including the energy, entropy, contrast, correlation, deficit 14 eigenvalues program.
mi-(2)
- 幂法是一种计算矩阵主特征值(矩阵按模最大的特征值)及对应特征向量的迭代方法, 特别是用于大型稀疏矩阵。 -The power method is a method of calculating the matrix eigenvalue (matrix largest characteristic value) and the iterative method of the corresponding feature vector, particularly for large spars
matlab-image-process
- comparehist是用于检测两个图像的直方图巴士距离，xuefu是通过C类均值算法对图像进行颜色聚类，ccv是提取衣服图像的颜色一致向量，便于以后对图像各个特征值进行操作-comparehist is used to detect the two image histogram bus distance, xuefu Class C means algorithm for image color clustering, ccv extract clothes image consistent
eigFEM
- 给定结构的刚度矩阵和质量矩阵,利用特征值分析计算出特征值和特征向量.-Given the structural stiffness and mass matrices, using eigenvalue analysis to calculate the eigenvalues and eigenvectors.
grid_study
- grid-study 学习文件，提取特征值写入features.txt 文件 recognition 识别文件，记录错误到 log.txt features.txt 为10*16 特征值 log.txt 为识别错误记录 study.txt 为学习图片的正确值 test.txt 为测试图片的正确值-grid-study learning file, extract the eigenvalue write the features.txt file
study
- study 学习文件，提取特征值写入features.txt 文件 recognition 识别文件，记录错误到 log.txt features.txt 为特征值记录文件 log.txt 为识别错误记录 study.txt 为学习图片的正确值 test.txt 为测试图片的正确值-study studying the documents, extract eigenvalue write features.txt file recognitio
recognition
- study 学习文件，提取特征值写入features.txt 文件 recognition 识别文件，记录错误到 log.txt features.txt 为特征值记录文件 log.txt 为识别错误记录 study.txt 为学习图片的正确值 test.txt 为测试图片的正确值-study studying the documents, extract eigenvalue write features.txt file recognitio
77grid
- grid-study 学习文件，提取特征值写入features.txt 文件 recognition 识别文件，记录错误到 log.txt features.txt 为10*49 特征值 log.txt 为识别错误记录 study.txt 为学习图片的正确值 test.txt 为测试图片的正确值-grid-study learning file, extract the eigenvalue write the features.txt file
BP
- grid-study 学习文件，提取特征值写入features.txt 文件 recognition 识别文件，记录错误到 log.txt features.txt 为10*49 特征值 log.txt 为识别错误记录 study.txt 为学习图片的正确值 test.txt 为测试图片的正确值-grid-study learning file, extract the eigenvalue write the features.txt file
cond_num
- matlab实现矩阵的特征值求解并讨论其在不同条件下的数值稳定性-matlab achieve matrix eigenvalue solution and discuss its numerical stability under different conditions.
matrix
- 实现了矩阵中的各种操作， 包括矩阵相加，相减，矩阵乘法，矩阵转秩，余子式，求行列式的值，求矩阵特征值，LU 分解，QR 分解，求现行方程组的解等等。 是任何做科学计算工作者必备的类库。 此类库也是C++初学者极好的参考资料。类库的实现运用了运算符重载，友元，异常处理，文件输入输出，函数重载，指针，动态分配内存等一系列C++技术。-Matrix in a variety of operations, including matrix addition, subtraction,
Wang_PCA
- 、去均值 2、计算协方差矩阵及其特征值和特征向量 3、计算协方差矩阵的特征值大于阈值的个数 4、降序排列特征值 5、去掉较小的特征值 6、去掉较大的特征值(一般没有这一步） 7、合并选择的特征值 8、选择相应的特征值和特征向量 9、计算白化矩阵 10、提取主分量 -To mean the number of calculated co-covariance matrix and its eigenvalues and eigenvectors to calculate
10_23
- 乘幂法C语言编程实现代码乘幂法是计算按模最大的一个或几个特征值（成为优势特征值）和相应特征向量的方法-Multiply the power method C language programming code exponentiation method is calculated according to one or several of the largest eigenvalue (became the dominant eigenvalues) and the corresponding
lossy
- In mode analysis it is usually the primary goal to find a propagation constant. This quantity is often, but not always, real valued if the analysis involves some lossy part, such as a nonzero conductivity or an open boundary, the eigenvalue is co
shuzhifenxi
- 使用幂法和反幂法求矩阵的特征值和特征向量-Power method and the inverse power method for matrix eigenvalue and eigenvectors
Kennedy_data_prepare
- 以一副高光谱遥感图像为例，将有值的像素点按类别排列为矩阵，行为元素，列为特征值，为下一步的数据处理做好准备-A hyperspectral remote sensing image, for example, the value of pixels arranged by category matrix, behavioral elements as eigenvalue, ready for the next step in the data processing