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/194440/8194227
m dispavgstd.m
function dispavpstd(cvpavg, cvpstd)
f=gcf;
figure('menubar','none')
[nshots tmp] = size(cvpavg);
shots = 1:nshots;
% plot(cvpstd(:,1));
% hold on;
% plot(cvpavg(:,1));
errorbar(cvpavg(:,1), shots
www.eeworm.com/read/194440/8194336
m dispplust.m
function dispplust
% Display of the average Plus Time values with their
% corresponding standard deviation and fold for each receiver
f=gcf;
fbcoord=refdata('get','fbcoord');
plust=refdata('get','plus
www.eeworm.com/read/192744/8286455
txt d9r1.txt
Private Sub Command1_Click()
'PROGRAM D9R1
'Driver for routine FIT
NPT = 100
SPREAD = 0.5
Dim X(100), Y(100), SIG(100)
IDUM& = -117
For I = 1 To NPT
X(I) =
www.eeworm.com/read/393436/8287394
m normpdfm.m
function o = normpdfM(x,m,s)
%Computes elementwise normal pdfs at x with mean m and standard
%deviation s
%Constant term
if nargin == 2
s = 1;
elseif nargin == 1
s = 1;
m = 0;
end
o =
www.eeworm.com/read/173453/9657340
m add_noise.m
function[sigma] = add_noise(waveform, EbN0db, rate, a) % waveform is input data, EbNOdb is set by user, rate is the data rate, a is fam.
en = 10^(EbN0db/10); % convert Eb/N0 from unit db to n
www.eeworm.com/read/173140/9670759
m normal.m
function y=normal(x,m,s)
% FUNCTION y=NORMAL(x,m,s)
% Gaussian distribution
% m=mean
% s=standard deviation
y=(1/sqrt(2*pi*s^2))*exp(-((x-m).^2)/(2*s^2));
www.eeworm.com/read/173140/9670798
m normal.m
function y=normal(x,m,s)
% FUNCTION y=NORMAL(x,m,s)
% Gaussian distribution
% m=mean
% s=standard deviation
y=(1/sqrt(2*pi*s^2))*exp(-((x-m).^2)/(2*s^2));
www.eeworm.com/read/415086/11084401
m colstd.m
% Standard deviation of the columns of a. Matlab's 'std' does the wrong thing when a has only one row
function a = colstd(a)
if size(a, 1) > 1
a = std(a);
else
a = zeros(size(a));
en
www.eeworm.com/read/414455/11111530
m normal.m
function y=normal(x,m,s)
% FUNCTION y=NORMAL(x,m,s)
% Gaussian distribution
% m=mean
% s=standard deviation
y=(1/sqrt(2*pi*s^2))*exp(-((x-m).^2)/(2*s^2));
www.eeworm.com/read/268231/11148919
m normal.m
function y=normal(x,m,s)
% FUNCTION y=NORMAL(x,m,s)
% Gaussian distribution
% m=mean
% s=standard deviation
y=(1/sqrt(2*pi*s^2))*exp(-((x-m).^2)/(2*s^2));