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Covarianc_matrix_transform
- 协方差计算，矩阵的协方差计算，可以用来进行分类，确定点直接的空间相似性-Covariance terms, the covariance matrix, the classification can be used to determine the points of similarity space directly
covK_L
- 根据两类训练集样本分别计算协方差矩阵作为产生矩阵进行K-L变换，与一般的整体产生的产生矩阵进行K-L变换只是存在向量上的平移-According to two kinds of training set samples separately calculated covariance matrix as produced by k-l transform matrix, and the whole of general produced by k-l matrix transformation
cov2para
- This MATLAB code computes the covariance matrix of a random variable
fc319646f828
- Evaluate the multi-variate density with mean vector m and covariance matrix C for the input vector x.-Evaluate the multi-variate density with mean vector m and covariance matrix C for the input vector x.
paper1007
- 利用样本协方差矩阵特征值分解实现双通道SAR动目标检测.pdf-Dual Channels SAR Ground Moving Target Detection with Eigen-decomposition of the Sample Covariance Matrix
Smart-antenna
- 智能天线类程序，分别有lms波束形成算法以及协方差矩阵求逆波束形成算法-Smart antenna class program, respectively lms beamforming algorithm as well as the covariance matrix inverse beamforming algorithm
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
1.MUSIC--MATLAB
- 基于天线阵列协方差矩阵的特征分解类DOA估计算法中，MUSIC算法具有普遍的适用性，只要已知天线阵的布阵形式，无论是直线阵还是圆阵，不管阵元是否等间隔分布，都可以得到高分辨的估计结果。-DOA estimation algorithm, MUSIC algorithm has universal applicability of decomposition classes based on the characteristics of the antenna array covariance m
purecmaes
- Covariance Matrix Adaptation CMA-ES
glasso
- Matlab implementation of the graphical Lasso model for estimating sparse inverse covariance matrix (a.k.a. precision or concentration matrix)
pca
- 主成分分析（Principal Copmponent Analysis，简称PCA）是一种常用的机遇变量协方差矩阵对信息进行处理、压缩和提取的有效方法。主成分分析，这种方法可以有效的找出数据中最“主要”的元素和结构，去除噪音和冗余，将原有的复杂数据降维，能够发掘出隐藏在复杂数据背后的简单结构。-PCA (Principal Copmponent Analysis, abbreviated PCA) is a commonly used covariance matrix Opportunity
ML.m
- 在贝叶斯分类中,用极大似然估计法估计概率分布的均值和方差-Compute the maximum-likelihood estimate of the mean and covariance matrix of each class and then uses the results to construct the Bayes decision region. This classifier works well if the classes are uni-modal, even when
BIDIRECTIONAL_SMOOTHNESS_MUSIC
- MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。-MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of vie
PCA1
- pca 神经网络 求样本协方差矩阵的特征值和特征向量 样本的均值化为零-pca neural network seeking sample covariance matrix of the eigenvalues and eigenvectors of the sample mean of zero
MIMO_doa_mvm
- 使用协方差矩阵的方法对MIMO的DOA进行估计，从而得到copon的DOA算法-Covariance matrix using the method of MIMO DOA estimation, resulting copon DOA Algorithms
mvdr
- 接受信号协方差矩阵估计的mvdr自适应算法。 方向图方针效果图-Receiving the signal covariance matrix estimation mvdr adaptive algorithm. Pattern renderings policy
cluCormar
- 用杂波协方差矩阵估计输入信号协方差矩阵的方法（输入为杂波和导向适量）-Noise covariance matrix estimated using the input signal covariance matrix method (input amount of clutter and orientation)
power-flow
- 电网内的多个风电场风速往往因为其地理位置的远近而有着不同程度的相关性，采用Ｎａｔａｆ 逆变换技术即可建立不同风电场之间具有相关性的风速分布样本空间，进而得到具有相关性的风 电场出力。在仿真过程中考虑风速的不确定性，将每个风电场出力视为一个负的满足威布尔随机 分布的负荷，根据历史数据，用方差—协方差矩阵描述不同风电场相关系数，建立最优潮流模型。 最后，在风电接入改进ＩＥＥＥ ３０及ＩＥＥＥ １１８节点系统中应用蒙特卡洛仿真计算，定量研究随着风 电场之间相关性的增强，最优潮流结果
MUSIC-algorithm
- 基于天线阵列协方差矩阵的特征分解类DOA估计算法-Based on the characteristics of the antenna array covariance matrix decomposition type of DOA estimation algorithm
2DPca
- 该方法基于二维矩阵得到图像协方差矩阵，比较精确，而且耗时短。-The method based on two-dimensional matrix image of covariance matrix, more precise, and time is short.