Covariance
共 14 篇文章
Covariance 相关的电子技术资料，包括技术文档、应用笔记、电路设计、代码示例等，共 14 篇文章，持续更新中。
Probability and Random Processes
Many good textbooks exist on probability and random processes written at the under-<br />
graduate level to the research level. However, there is no one handy and ready book<br />
that explains most o
Fast DOA Estimation Algorithm using Pseudo Covariance Matrix的程序
Fast DOA Estimation Algorithm using Pseudo Covariance Matrix的程序
使用INTEL矢量统计类库的程序,包括以下功能:  Raw and central moments up to 4th order  Kurtosis and
使用INTEL矢量统计类库的程序,包括以下功能:
 Raw and central moments up to 4th order
 Kurtosis and Skewness
 Variation Coefficient
 Quantiles and Order Statistics
 Minimum
又一种增量人脸学习算法——参考文献“Candid Covariance-Free Incremental Principal Component Analysis.”
又一种增量人脸学习算法——参考文献“Candid Covariance-Free Incremental Principal Component Analysis.”
EKF-SLAM Simulator This version of the simulator uses global variables for all large objects, suc
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 MatLa
Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the princ
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 variabl
runs Kalman-Bucy filter over observations matrix Z for 1-step prediction onto matrix X (X can = Z)
runs Kalman-Bucy filter over observations matrix Z
for 1-step prediction onto matrix X (X can = Z)
with model order p
V = initial covariance of observation sequence noise
returns model parameter e
function y_cum = cum2x (x,y, maxlag, nsamp, overlap, flag) ％CUM2X Cross-covariance ％ y_cum = cum2x
function y_cum = cum2x (x,y, maxlag, nsamp, overlap, flag)
％CUM2X Cross-covariance
％ y_cum = cum2x (x,y,maxlag, samp_seg, overlap, flag)
％ x,y - data vectors/matrices with identical dimensions
％
A series of .c and .m files which allow one to perform univariate and bivariate wavelet analysis of
A series of .c and .m files which allow one to perform univariate and bivariate wavelet analysis of discrete time series. Noother wavelet package is necessary -- everything is contained in this archiv
The angles in degrees of the two spatially propagating signals Compute the array response vectors o
The angles in degrees of the two spatially propagating signals
Compute the array response vectors of the two signals
Compute the true covariance matrix
Knowledge of the process noise covariance matrix is essential for the application of Kalman filteri
Knowledge of the process noise covariance matrix
is essential for the application of Kalman filtering. However,
it is usually a difficult task to obtain an explicit expression of
for large time var
This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise
This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the s
寻找函数的全局极小值
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 source
％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input da
％ EM algorithm for k multidimensional Gaussian mixture estimation
％
％ Inputs:
％ X(n,d) - input data, n=number of observations, d=dimension of variable
％ k - maximum number of Gaussian components a