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disp_rand
- 本程序用matlab生成白噪声，并且基于一个离散线性随机系统的模型生成了y(k)和x(k)，绘制出了x(k|k-1)和x(k)的对比曲线，求出了提前一步预报的误差协方差阵的稳定值-the procedures used Matlab generate white noise, and on a discrete linear stochastic systems model generated y (k) and x (k), mapping out the x (k | k-1) and x
global_mini
- 寻找函数的全局极小值，global minimization of contrast function with random restarts the data are assumed whitened (i.e. with identity covariance matrix). The output is such that Wopt*x are the independent sources.-Find function of the minimum value of the overa
pca.m
- 本程序的运行环境为matlab6.5，在command window下输入数据x和a，然后调用函数pca（x，a）（即本程序的主程序）输入的两个参数的意义是：一个是样本数据x，另外一个是主成分累积贡献率的一个闸值，作为选定主成分个数的一个重要数据。 即可得到样本的协方差矩阵，相关矩阵，相关矩阵的特征根及特征向量，主成分个数和主成分负荷矩阵。 -the procedures for the environment matlab6.5. under the command window i
GHWPCA
- VC 6.0下的主成分分析代码，包括关系矩阵，协方差矩阵，以及因子分析的功能-VC 6.0 Principal Component Analysis code, including the relationship matrix, covariance matrix, and the function of factor analysis
rtejfgds
- 现有的代数特征的抽取方法绝大多数采用一维的方法，即首先将图像转换为一维向量，再用主分量分析（PCA）,Fisher线性鉴别分析（LDA）,Fisherfaces式核主分量分析（KPCA）等方法抽取特征，然后用适合的分类器分类。针对一维方法维数过高，计算量大，协方差矩阵常常是奇异矩阵等不足，提出了二维的图像特征抽取方法，计算量小，协方差矩阵一般是可逆的，且识别率较高。-existing algebra feature extraction method using a majority of th
ppca
- Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the principal ％ component subspace U of dimension PPCA_DIM using a centred covariance matrix X. The variable VAR contains the off-subspace variance (which
ekf
- EKF-SLAM Simulator This version of the simulator uses global variables for all large objects, such as the state covariance matrix. While bad programming practice, it is a necessary evil for MatLab efficiency, as MatLab has no facility to
EnsembleKalman_filter
- 集合卡尔曼滤波(EnKF) 数据同化方法可以避免了EKF 中协方差演变方程预报过程中出现的计算不准确和关于协方差矩阵的大量数据的存储问题,最主要的是可以有效的控制估计误差方差的增长,改善预报的效果。-Ensemble Kalman Filter (EnKF) data assimilation methods can be avoided in the EKF covariance forecasting the evolution equation arising in the course
rsvd
- 基于GM算法和QR分解实现的稳健奇异值分解算法，通过该算法可以获取一个数居阵的稳健方差－协方差阵。在该稳健方差－协方差阵上可以进行诸如，稳健主成份分解、稳健聚类、稳健因子分析等操作。-GM based on QR decomposition algorithm and the realization of the stability of singular value decomposition algorithm, the algorithm can be accessed through a
direct_kim
- Fast DOA Estimation Algorithm using Pseudo Covariance Matrix的程序-Fast DOA Estimation Algorithm using Pseudo Covariance Matrix procedure
sim
- 实现对自适应波束形成SIM算法的仿真，在该程序中，我们先设置入射的信号，再进行互协方差矩阵和自协方差矩阵的求解来实现该算法-To achieve adaptive beamforming algorithm for the simulation of SIM, in the process, we first set up the incident signal and then cross-covariance matrix and covariance matrix from the sol
SENSEgfactorcalculation
- 计算SENSE重建图像中的g-factor,这是并行磁共振成像SENSE算法的关键一步-G-factor is the metric to quantify the amplificaiton of noise power in reconstructing SENSE accelerated image. The detail was presented in Pruessmann s 1999 Magn. Reson. Med. paper. In theory, g-factor is t
5
- 一种Kalman滤波系统误差及其协方差矩阵的半参数估计方法的研究文章-A Kalman filter system error covariance matrix and the semi-parametric estimation methods of research papers
Matlabcodes-RobustPCA
- Matlab codes for Robust PCA multivariate control chart-Robust PCA multivariate control chart mainly consists two steps: Step1 Calculates the robust mean and the robust covariance of original dataset using the minimum covariance determinant (M
strcov
- Structured covariance estimation. The routine takes a covariance matrix as input and returns the Toeplitz matrix that lies closest to it, in the sense that it minimizes the Kullback-Leibler divergence between the two. Input must be a real, square, sy
SMI
- 块自适应处理算法先有采样快拍数据计算采样协方差矩阵，再来计算自适应权矢量。典型的块自适应处理算法为采样矩阵求逆(SMI)算法。仿真了采样矩阵求逆法(SMI)的波束形成方向图旁瓣的高低受信号快拍数的影响。-Block adaptive processing algorithms prior sample snapshot data of the sampling covariance matrix, again computing adaptive weight vector. A typical
34535
- 导航系统误差及其协方差阵的随机加权拟合.-Navigation system errors and the covariance matrix of random weighted fit.
covariance-matrix
- 协方差矩阵的编程,通过这个程序可以计算协方差，-programme of covariance matrix，Through this program can calculate the covariance
matrix
- 求协方差矩阵（C++） -Covariance matrix (C++) covariance matrix (C++)
usefultool
- 计算协方差提供了便利，特别是考虑了半衰期；同时提供了一些其他常用的计算工具，例如decayma ewma等移动平滑计算；(It is convenient to calculate covariance, especially considering half-life. Some other common computing tools, such as decayma ewma and other mobile smoothing calculations, are also provide