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MatrixCalculator
- 2.1 矩阵类设计 2.2 矩阵基础运算 2.3 实矩阵求逆的全选主元高斯-约当法 2.4 复矩阵求逆的全选主元高斯-约当法 2.5 对称正定矩阵的求逆 2.6 托伯利兹矩阵求逆的特兰持方法 2.7 求行列式值的全选主元高斯消去法 2.8 求矩阵秩的全选主元高斯消去法 2.9 对称正定矩阵的乔里斯基分解与行列式的求值 2.10 矩阵的三角分解 2.11 一般实矩阵的QR分解 2.12 一般实矩阵的奇异值分解 2.13 求广义
Time-frequency-atom-
- 时频原子分解算法利用冗余特性分解成多个时频原子库来进行信号特征的处理分析-Time-frequency atom decomposition algorithm using redundant features broken down into processing and analysis the multiple frequency atoms library to signal characteristics
Time-frequency-atom-program
- 时频原子分解主要用于建立时频原子库,从而根据明显的特征提取出信号-Time-frequency atom decomposition is mainly used to establish the time-frequency atoms library, which according to the obvious features extracted signal
Tutor
- 时频原子分解算法主要用于建立时频原子库,从而提取出特征信号-Time-frequency atom decomposition algorithm for frequency atoms library created to extract the characteristic signal
Decomposition
- 时频原子分解算法主要用于建立时频原子库,从而提取出特征信号-Time-frequency atom decomposition algorithm for frequency atoms library created to extract the characteristic signal
convwavepacket_fenjie
- 这是自己编的卷积型小波包的分解程序,用于机械故障特征提取,实现了克服Mallat算法数据量减少和产生虚假频率的缺陷-Own series of convolution type of wavelet packet decomposition procedures for mechanical fault feature extraction to overcome the defects of the the Mallat algorithm decrease in the amount of
wavelet-packet-de_re
- 用小波工具箱函数实现小波包的分解与重构,非常适合与机械故障特征提取。-Wavelet packet decomposition and reconstruction, and is ideal for mechanical fault feature extraction using wavelet toolbox functions.
emd
- 经验模态分解方法简称EMD方法。该方法从本质上讲是对一个信号进行平稳化处理,其结果是将信号中真实存在的不同尺度波动或趋势逐级分解开来,产生一系列具有不同特征尺度的数据序列。-Empirical mode decomposition method is referred to as the EMD method. This method is in essence a signal smoothing processing, the result is the real signal differ
Hausdorff_Distance
- 提出了利用小波分解建立多分辨率图像锥和Hausdorff距离的医学图像配准方法。先利用小波方法建立多分辨率图像锥, 然后根据梯度向量幅度提取分层图像的特征点, 利用Hausdorff距离进行特征点集的匹配。该方法提高了配准的速度和精度, 而且具有鲁棒性。-Image registration is the matching processing in which two or more images match from the same scene derived from different
WAVE-weifengyin
- 小波变换具有多分辨率分析的特点,并且在时频两域都具有表征信号局部特征的能力。小波变换通过将时间系列分解到时间频率域内,从而得出时间系列的显著的波动模式,即周期变化动态,以及周期变化动态的时间格局(Torrence and Compo, 1998)。小波(Wavelet),即小区域的波,是一种特殊的、长度有限,平均值为零的波形。它有两个特点:一是“小”,二是具有正负交替的“波动性”,即直流分量为零。小波分析是时间(空间)频率的局部化分析,它通过伸缩平移运算对信号(函数)逐步进行多尺度细化,能自动适
Desktop
- 特征空间 旋转矢量波束形成算法 通过采样矩阵不用分解波束的形成-Feature space rotation vector beamforming algorithm without decomposition of the beam through the sample matrix formation
bemd
- 二维EMD程序,这是利用最新的插值函数,个比较经典的二维经验模式分解程序代码,适用于图像的特征提取和分解 -。-A two-dimensional EMD algorithm, the author is Anna Linderhed, her Ph.D. research topic is bidimensional EMD and wavelet transform
EOF
- 经验正交函数分解,求时空场f(m,n)的特征向量egvt(m,mnl),时间系数ecof(mnl,n),特征值er(mnl,1),累积特征值er(mnl,2),解释方差er(mnl,3),累积解释方差er(mnl,4)-Empirical orthogonal function, f (m, n) seeking spacetime the eigenvectors egvt (m, MNL), the time coefficient ecof (MNL, n), the characteri
nmf
- 基于非负矩阵分解(NMF)的人脸特征提取算法,其基本思想是找到一个母性子空间,是的构成子空间的基图像的像素点都是正值-algorithm of NMF of face detection by matlab
package_emd
- 经验模态分解代码,依据数据自身的时间尺度特征来进行信号分解,无须预先设定任何基函数。-Empirical mode decomposition code, based on the data of their characteristic time scale for signal decomposition, no need of any of a set of basis function.
2dwave
- 使用二维小波进行分解,再进行重构的程序。重要用于人脸特征提取。-Using two-dimensional wavelet decomposition remodeling program. Important for face feature extraction.
shuzhifenxi2
- 对矩阵拟上三角化,并且对矩阵进行QR分解,从而求出矩阵的特征值以及特征向量。-Matrix intend on triangulation, and matrix QR decomposition, and thus find the eigenvalues and eigenvectors of the matrix.
renliantezhengdingwei
- 文章在小波分析的基础上,提出了一种在图像的小波分解数据域中实现对称变换的方法, 并把这种方法运用于人脸特征的定位,这种方法可以提高人脸特征定位的效率。-Based on wavelet analysis, the article proposes a wavelet decomposition of the image data domain symmetry transformation method, and this method is applied to the positioni
330
- 提出了将信号进行相空间重构后再采用奇异值分解, 对分解后的主成分进行包络分析, 从而提取信号的隐含特 征的方法, 并将该方法应用于齿轮的局部故障振动特征信号的提取中。数值仿真实验结果表明, 该方法能有效提取强背景 信号及噪声中的弱冲击特征信号, 是一种有效的弱信号特征提取方法。采用该方法对齿轮振动信号进行故障特征提取与识 别, 结果与实际情况相符。-Signal implicit characteristic of phase space reconstruction, and th
emd
- emd 方法可将一些非线性信号分解成若干个信号,从而方便您对分解后的信号作特征提取。-emd method of nonlinear signal decomposed into a number of signals, and thus easy to extract the signal for the characteristics of the decomposition.