代码搜索：deviation
找到约 1,443 项符合「deviation」的源代码
代码结果 1,443
www.eeworm.com/read/287843/8664751
m gwnoise.m
function [m, d, s] = gwnoise(m, d, s)
%GWNOISE generate valid mean value, standard deviation and seeds for GWNOISE block.
% [M, D, S] = GWNOISE(M, D, S) checks input mean M, standard deviation D, an
www.eeworm.com/read/428849/8834431
m gencircledata.m
function [X,gnd_X] = gencircledata(Center,R,num_data,dev)
% GENCIRCLEDATA Generates data on circle corrupted by Gaussian noise.
%
% Synopsis:
% [X,gnd_X] = gencircledata(Center,R,num_data,dev)
www.eeworm.com/read/362246/10009876
m gencircledata.m
function [X,gnd_X] = gencircledata(Center,R,num_data,dev)
% GENCIRCLEDATA Generates data on circle corrupted by Gaussian noise.
%
% Synopsis:
% [X,gnd_X] = gencircledata(Center,R,num_data,dev)
www.eeworm.com/read/280595/10311522
m gencircledata.m
function [X,gnd_X] = gencircledata(Center,R,num_data,dev)
% GENCIRCLEDATA Generates data on circle corrupted by Gaussian noise.
%
% Synopsis:
% [X,gnd_X] = gencircledata(Center,R,num_data,dev)
www.eeworm.com/read/272476/10956550
m psd_burg.m
function [ap_burg, en_burg] = psd_burg(xn, p);
%[ap_burg, en_burg] = psd_burg(xn, p) use the burg
%method to estimate the psd of signal xn with a p phase AR model
%ap_burg is the AR coiefficients
www.eeworm.com/read/449504/7501951
m timing_tst.m
% timing tests for chi-squared deviation generation
n = 3000;
tic;
for i=1:1500;
out = chi2rnd(4,n,1);
end;
toc;
tic;
for i=1:1500;
out = rchisq(n,4);
end;
toc;
www.eeworm.com/read/439815/7701256
m gwnoise.m
function [m, d, s] = gwnoise(m, d, s)
%GWNOISE generate valid mean value, standard deviation and seeds for GWNOISE block.
% [M, D, S] = GWNOISE(M, D, S) checks input mean M, standard deviation D, an
www.eeworm.com/read/299459/7849925
m gencircledata.m
function [X,gnd_X] = gencircledata(Center,R,num_data,dev)
% GENCIRCLEDATA Generates data on circle corrupted by Gaussian noise.
%
% Synopsis:
% [X,gnd_X] = gencircledata(Center,R,num_data,dev)
www.eeworm.com/read/333375/12685340
m surethresh2.m
function [x,thresh] = SUREThresh2(y)
%
%%%%%%It's My Own Function!!!
%
% SUREThresh2 -- Adaptive Threshold Selection Using Principle of SURE for 2-D Signal
% Usage
% thresh = SUREThresh2(y)
www.eeworm.com/read/244937/12830174
m gwnoise.m
function [m, d, s] = gwnoise(m, d, s)
%GWNOISE generate valid mean value, standard deviation and seeds for GWNOISE block.
% [M, D, S] = GWNOISE(M, D, S) checks input mean M, standard deviation D, an