代码搜索：Variance
找到约 2,271 项符合「Variance」的源代码
代码结果 2,271
www.eeworm.com/read/143595/12857975
tex hrest.tex
%/* ----------------------------------------------------------- */
%/* */
%/* ___ */
www.eeworm.com/read/143595/12858020
tex hcompv.tex
%/* ----------------------------------------------------------- */
%/* */
%/* ___ */
www.eeworm.com/read/142092/12963058
m dst.m
function z=dst(nt,dt,nzp)
% The function DST analyzes the degree of stationarity of data nt(n,m) by
% calculating the variance for each n, where n specifies the number
% of frequency values, an
www.eeworm.com/read/142034/12968952
m tfpm_simu_generate_tfma1.m
x= tfarma_gen(randn(N, 1), 1, par, 1/2);
v= sqrt(variance)*randn(N, 1);
y= x+v;
www.eeworm.com/read/137160/13341798
m pca.m
%PCA Principal component analysis (PCA or MCA on overall covariance matrix)
%
% [W,FRAC] = PCA(A,N)
% [W,N] = PCA(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Number of dimensions
www.eeworm.com/read/314653/13562205
m pca.m
%PCA Principal component analysis (PCA or MCA on overall covariance matrix)
%
% [W,FRAC] = PCA(A,N)
% [W,N] = PCA(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Number of dimensions
www.eeworm.com/read/493294/6399879
m pca.m
%PCA Principal component analysis (PCA or MCA on overall covariance matrix)
%
% [W,FRAC] = PCA(A,N)
% [W,N] = PCA(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Number of dimensions
www.eeworm.com/read/400577/11572580
m pca.m
%PCA Principal component analysis (PCA or MCA on overall covariance matrix)
%
% [W,FRAC] = PCA(A,N)
% [W,N] = PCA(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Number of dimensions
www.eeworm.com/read/157396/11712758
tex hrest.tex
%/* ----------------------------------------------------------- */
%/* */
%/* ___ */