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/480200/6668093
cpp prodsamplegibbsms.cpp
///////////////////////////////////////////////////////
// Functions for single-scale gibbs samplers
//
///////////////////////////////////////////////////////
//
// Written by Alex Ihler and Mik
www.eeworm.com/read/405084/11472035
m fig9_28.m
clear all
npts = 2000;
del = 1/2000;
t = 0:del:1;
inp = (1+.2 .* t + .1 .*t.^2) + cos(2. * pi * 2.5 .* t);
X0 = [1,.1,.01]';
% it is assumed that the measurement vector H=[1,0,0]
% this is the
www.eeworm.com/read/405084/11472076
m fig9_27.m
clear all
npts = 2000;
del = 1/2000;
t = 0:del:1;
inp = (1+.2 .* t + .1 .*t.^2);% + cos(2. * pi * 2.5 .* t);
X0 = [1,.1,.01]';
% it is assumed that the measurmeny vector H=[1,0,0]
% this is the
www.eeworm.com/read/402117/11542982
m fig9_28.m
clear all
npts = 2000;
del = 1/2000;
t = 0:del:1;
inp = (1+.2 .* t + .1 .*t.^2) + cos(2. * pi * 2.5 .* t);
X0 = [1,.1,.01]';
% it is assumed that the measurement vector H=[1,0,0]
% this is the
www.eeworm.com/read/402117/11543023
m fig9_27.m
clear all
npts = 2000;
del = 1/2000;
t = 0:del:1;
inp = (1+.2 .* t + .1 .*t.^2);% + cos(2. * pi * 2.5 .* t);
X0 = [1,.1,.01]';
% it is assumed that the measurmeny vector H=[1,0,0]
% this is the
www.eeworm.com/read/402094/11543191
m lsar.m
function [a,sig2]=lsar(y,n)
%
% The Least-Squares AR method (the covariance method)
% given by equation (3.4.14) with N1=n+1 and N2=N.
%
% call [a,sig2]=lsar(y,n);
%
% y -> the data vector
%
www.eeworm.com/read/402094/11543204
m yulewalker.m
function [a,sig2]=yulewalker(y,n)
%
% The Yule-Walker method for AR spectral estimation, given
% by equation (3.4.2).
%
% [a,sig2]=yulewalker(y,n);
%
% y -> the data vector
% n -> AR
www.eeworm.com/read/401480/11557280
m fig9_28.m
clear all
npts = 2000;
del = 1/2000;
t = 0:del:1;
inp = (1+.2 .* t + .1 .*t.^2) + cos(2. * pi * 2.5 .* t);
X0 = [1,.1,.01]';
% it is assumed that the measurement vector H=[1,0,0]
% this is the
www.eeworm.com/read/401480/11557322
m fig9_27.m
clear all
npts = 2000;
del = 1/2000;
t = 0:del:1;
inp = (1+.2 .* t + .1 .*t.^2);% + cos(2. * pi * 2.5 .* t);
X0 = [1,.1,.01]';
% it is assumed that the measurmeny vector H=[1,0,0]
% this is the
www.eeworm.com/read/400577/11572901
m var.m
%VAR Dataset overload
%
% [V,U] = VAR(A,W)
%
% Computes variance V and mean U in a single run for consistency with datafile overload.