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DetectionMethodofFabricDefecBasedonWaveletEntropy.
- 在采用二维离散小波变换对织物图像进行分解的基础上，引入了熵的概念，将小波熵作为织物图像的特征值，把熵值看作系统紊乱程度的度量，由此得到织物图像的小波熵特征值，通过与正常织物经过二维小波变换后提取的小波熵值相比较，熵值大者即认为有疵点存在-At the use of two-dimensional discrete wavelet transform decomposition of the fabric image, based on the introduction of the concep
EIGENR
- SUBROUTINE TO FIND ALL REAL EIGENVALUES & EIGENVECTORS OF A REAL MATRIX [A]nxn 1. Characteristic Polynomial by the Leverrier Method 2. Eigenvalues (roots) of the Characteristic Polynomial by the Bairstow Method 3. Eigenvectors by t
Cpp1
- 用幂法和反幂法实现求矩阵的特征值和特征向量-With the power method and inverse power law to achieve demand matrix eigenvalues and eigenvectors
Matrix_Pencil
- 出一种实现不同维间估计结果自动配对的二维频率估计算法。首先把二维频率估计问题转化成两个矩阵束的特征值问题。根据矩阵束的特征求出两个矩阵束的公共特征向量，并以此为基础同时求出两个矩阵束的特征值。算法估计误差与现有算法相近，但解决了现有算法普遍存在的配对难题。 -Matrix pencils play an important role in numerical linear algebra. The problem of finding the eigenvalues of a pencil
Complex_SVD_algorithm_for_Cplus
- To do complex SVD for non-codebook precoding in open loop spatial multiplexing in MIMO, Householder Reduction and QR Diagonalization is applied to H matrix to obtain eigenvalues and eigenvectors of matrix.
Plane61bar
- 平面61绗架结构动力特性分析，分别采用三种方法计算结构的前9阶频率。-To compyte the first nine eigenvalues of plane 61-bar truss
0
- 利用主元分析和奇异值分解进行人脸特征提取的方法(并详细阐述其在PQRSQT中的实现过程(包括读取图像文件U计算均值脸U求特征值和特征向量(计算人脸特征参数-实现过程均给出了MATLAB代码-Using principal component analysis and singular value decomposition facial feature extraction method (and detail its in the PQRSQT in the implementation pr
VEERING
- An investigation of the effects of disorder on the modes of vibration of nearly periodic structures is presented. It is shown that, in structures with close eigenvalues, small structural irregularities result in both strong localization of the mode
si-band
- 这个程序可以计算硅的能带结构，里面包涵了求解本征函数，本征值，和本征态的代码-The program code can calculate the band structure of silicon, which bear solving eigenfunctions, eigenvalues and eigenstates
renlianhsib
- PCA 人脸识别修订版，识别率88％ 获取特征值及特征向量 word 可以参考 学习-PCA face recognition revision, the recognition rate of 88 Get the eigenvalues and eigenvectors word can refer to learning
CORDIC_Algorithms_and_architectures
- Digital signal processing (DSP) algorithms exhibit an increasing need for the e#cient implementation of complex arithmetic operations. The computation of trigonometric functions, coordinate transformations or rotations of complex valued phasors
irbleigs_svd
- 求解大型矩阵的特征值和特征向量irbleigs_svd-Solving large eigenvalues and eigenvectors irbleigs_svd
PCA_tutorial
- This tutorial is designed to give the reader an understanding of Principal Components Analysis (PCA). PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common techn
decompasition
- Eigenvalues and eigenvectors examples
EOF
- 一个方便实用的进行EOF程序，可对数据分析出相应的模态-and eigenvalues V. The most effecient algorithm proposed by von Storch and Hannostock (1984) is used.
NCS2011---146---autmented-reality
- 目前擴增實境技術相關應用大部分以使用標記為主，但各式應用需求與日俱增，無標記(markerless)擴增實境技術使用上更具彈性，不必受限於標記的使用，因此應用層面更廣。視覺追蹤技術是擴增實境系統重要底層核心技術之一，但使用視覺追蹤技術在實際應用上易受到追蹤物件本身及外觀變化之影響，因此本文提出適用於無標記擴增實境應用之物件追蹤方法，能有效追蹤各式真實物件。首先框選設定追蹤物件；接著擷取物件特徵值，藉由特徵值比對以持續追蹤物件，並利用金字塔L-K光流法以縮短比對運算時間；最後經由2D-3D座標轉換