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/252197/12293914
m ip_07_10.m
% MATLAB script for Illustrative Problem 10, Chapter 7.
clear
echo on
K=10;N=2*K;T=100;variance=1;
noise=sqrt(variance)*randn(1,N);
a=rand(1,36);
a=sign(a-0.5);
b=reshape(a,9,4);
% Generate th
www.eeworm.com/read/234502/14110984
m gaussianmask.m
function M = gaussianMask(k,s)
% k: the scaling factor
% s: standard variance
R = ceil(3*s); % cutoff radius of the gaussian kernal
for i = -R:R,
for j = -R:R,
M(i+ R+1,j+R+1) =
www.eeworm.com/read/228977/14356452
asv bootstrap.asv
function [x,q] = bootstrap(Ns,R,Q,initVar,numSamples);
% PURPOSE : This m file performs the bootstrap algorithm (a.k.a. SIR,
% particle filter, etc.) for the model specified in the
%
www.eeworm.com/read/228977/14356522
m bootstrap.m
function [x,q] = bootstrap(Ns,R,Q,initVar,numSamples);
% PURPOSE : This m file performs the bootstrap algorithm (a.k.a. SIR,
% particle filter, etc.) for the model specified in the
%
www.eeworm.com/read/227522/14421547
m y2res.m
function [R]=y2res(Y)
% Y2RES evaluates basic statistics of a data series
%
% R = y2res(y)
% several statistics are estimated from each column of y
%
% OUTPUT:
% R.N number of samples, NaNs ar
www.eeworm.com/read/227522/14421666
m hist2res.m
function [R]=hist2res(H,fun)
% Evaluates Histogram data
% [R]=hist2res(H)
%
% [y]=hist2res(H,fun)
% estimates fun-statistic
%
% fun 'mean' mean
% 'std' standard deviation
% 'var' variance
% 'sem' stan
www.eeworm.com/read/124283/14579148
c stat.c
#include
#include
int
main(void)
{
double data[5] = {17.2, 18.1, 16.5, 18.3, 12.6};
double mean, variance, largest, smallest;
mean = gsl_stats_mean(data, 1
www.eeworm.com/read/220187/14847314
txt 描述.txt
The script generates spatial data with a scale-invariant power spectrum (1/f noise) and a normal error distribution.
The spectral density of the data is proportional to f^BETA, where f is the frequ
www.eeworm.com/read/216045/15028721
m ip_07_10.m
% MATLAB script for Illustrative Problem 10, Chapter 7.
clear
echo on
K=10;N=2*K;T=100;variance=1;
noise=sqrt(variance)*randn(1,N);
a=rand(1,36);
a=sign(a-0.5);
b=reshape(a,9,4);
% Generate th
www.eeworm.com/read/213940/15121953
m ip_07_10.m
% MATLAB script for Illustrative Problem 10, Chapter 7.
echo on
K=10;N=2*K;T=100;variance=1;
noise=sqrt(variance)*randn(1,N);
a=rand(1,36);
a=sign(a-0.5);
b=reshape(a,9,4);
% Generate the 16QAM